From vsochat at gmail.com Mon Nov 2 12:57:32 2015 From: vsochat at gmail.com (vanessa s) Date: Mon, 2 Nov 2015 09:57:32 -0800 Subject: [Neuroimaging] nipy circle fixed! Message-ID: Hi everyone! Thanks to Ben's help, the last push was done so that our artifacts are previewing on circle, and everything is now set up as we wanted it! If you take a look at the custom URL change: https://github.com/nipy/nipy.github.com/blob/master/circle_urls.sh and the circle config: https://github.com/nipy/nipy.github.com/blob/master/circle.yml It was quite un-elegant. I've contacted circle multiple times about this, and the extent of their interest has been forwarding me to the community page, so they don't seem interested in making it any easier to preview jekyll sites. So if anyone has ideas for more elegant solutions, please share. Huge thanks Ben, you-da-man! :) Best, Vanessa -- Vanessa Villamia Sochat Stanford University '16 (603) 321-0676 -------------- next part -------------- An HTML attachment was scrubbed... URL: From davmazo at gmail.com Thu Nov 5 08:39:00 2015 From: davmazo at gmail.com (David Dalmazzo) Date: Thu, 5 Nov 2015 14:39:00 +0100 Subject: [Neuroimaging] help with dconn.nii file Message-ID: Hi, Not sure if this is the place for this question. I'm trying to read a big file (33GB) called HCP_S500_R468_MIGPd4500ROW.dconn.nii downloaded from HCP. I'm trying to extract the info of the correlation matrix using niBabel but after many hours (two days) trying, I'm still lost in the method. I don't make it by using the examples related to nifty-2 in the nibble documentation. I'm developing a software of brain activity visualization and the app started with Hagmann connectome data that is actually quite old, a colleague told me to use HCP connectome to update our models, that's why I'm now stocked trying to have a more complete connectome. Thanks for the help David -------------- next part -------------- An HTML attachment was scrubbed... URL: From effigies at bu.edu Sun Nov 8 09:43:50 2015 From: effigies at bu.edu (Christopher J Markiewicz) Date: Sun, 8 Nov 2015 09:43:50 -0500 Subject: [Neuroimaging] Upcoming nibabel bug fix release Message-ID: <563F5FA6.2080303@bu.edu> Hi all, Python 3.5, numpy 1.10, and the upcoming pydicom 1.0 are all taking the opportunity to break nibabel in little ways, so it seems like a good time to push out a bug-fix release (v2.0.2). Since 2.0.1, a lot of effort has gone into rearchitecting, and we (by which I mostly mean Ben Cipollini) are plugging along toward cleanly integrated Gifti and Cifti support. For simplicity, I'll be leaving that work out of the current release so that all of the relevant changes can be released at once. I'm doing the preparation work for 2.0.2 in GitHub issue 377 (https://github.com/nipy/nibabel/pull/377), so I'd appreciate as many eyes on it as can be spared. In particular, if there's a bug fix that I've failed to include, or if you have a bug to report, please let us know. There is one outstanding bug - breaking the Python 2.7 build on 32-bit Windows - that I would like to resolve before release, if anybody has thoughts: https://github.com/nipy/nibabel/pull/367 Thanks! -- Christopher J Markiewicz Ph.D. Candidate, Quantitative Neuroscience Laboratory Boston University From davmazo at gmail.com Mon Nov 9 05:48:44 2015 From: davmazo at gmail.com (David Dalmazzo) Date: Mon, 9 Nov 2015 11:48:44 +0100 Subject: [Neuroimaging] Upcoming nibabel bug fix release In-Reply-To: <563F5FA6.2080303@bu.edu> References: <563F5FA6.2080303@bu.edu> Message-ID: Hi all, Sound that new python version is not totally compatible with nibabel. My question is, it is possible to parse Cifti files from HCP using older version of Python? I found very complicated to resolve this task of extract connectome data from those files, not even with Matlab R2015b (8.6.0.267246) library fieldtrip is not working properly. Someone has a different technique to extract connectome matrix from .dconn.nii files? Thanks David On Sun, Nov 8, 2015 at 3:43 PM, Christopher J Markiewicz wrote: > Hi all, > > Python 3.5, numpy 1.10, and the upcoming pydicom 1.0 are all taking the > opportunity to break nibabel in little ways, so it seems like a good > time to push out a bug-fix release (v2.0.2). > > Since 2.0.1, a lot of effort has gone into rearchitecting, and we (by > which I mostly mean Ben Cipollini) are plugging along toward cleanly > integrated Gifti and Cifti support. For simplicity, I'll be leaving that > work out of the current release so that all of the relevant changes can > be released at once. > > I'm doing the preparation work for 2.0.2 in GitHub issue 377 > (https://github.com/nipy/nibabel/pull/377), so I'd appreciate as many > eyes on it as can be spared. In particular, if there's a bug fix that > I've failed to include, or if you have a bug to report, please let us know. > > There is one outstanding bug - breaking the Python 2.7 build on 32-bit > Windows - that I would like to resolve before release, if anybody has > thoughts: https://github.com/nipy/nibabel/pull/367 > > Thanks! > -- > Christopher J Markiewicz > Ph.D. Candidate, Quantitative Neuroscience Laboratory > Boston University > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From bcipolli at ucsd.edu Mon Nov 9 08:13:47 2015 From: bcipolli at ucsd.edu (Ben Cipollini) Date: Mon, 9 Nov 2015 05:13:47 -0800 Subject: [Neuroimaging] Upcoming nibabel bug fix release In-Reply-To: References: <563F5FA6.2080303@bu.edu> Message-ID: Hi David, CIFTI support is not complete in nibabel, so no way to do it in nibabel yet. Have you tried using the conversion tools inside of Connectome Workbench? Have you tried asking about the fieldtrip issue on the HCP email list? They tend to be very responsive. Ben On Mon, Nov 9, 2015 at 2:48 AM, David Dalmazzo wrote: > Hi all, > Sound that new python version is not totally compatible with nibabel. My > question is, it is possible to parse Cifti files from HCP using older > version of Python? I found very complicated to resolve this task of extract > connectome data from those files, not even with Matlab R2015b > (8.6.0.267246) library fieldtrip is not working properly. > Someone has a different technique to extract connectome matrix from > .dconn.nii files? > Thanks > > David > > On Sun, Nov 8, 2015 at 3:43 PM, Christopher J Markiewicz > wrote: > >> Hi all, >> >> Python 3.5, numpy 1.10, and the upcoming pydicom 1.0 are all taking the >> opportunity to break nibabel in little ways, so it seems like a good >> time to push out a bug-fix release (v2.0.2). >> >> Since 2.0.1, a lot of effort has gone into rearchitecting, and we (by >> which I mostly mean Ben Cipollini) are plugging along toward cleanly >> integrated Gifti and Cifti support. For simplicity, I'll be leaving that >> work out of the current release so that all of the relevant changes can >> be released at once. >> >> I'm doing the preparation work for 2.0.2 in GitHub issue 377 >> (https://github.com/nipy/nibabel/pull/377), so I'd appreciate as many >> eyes on it as can be spared. In particular, if there's a bug fix that >> I've failed to include, or if you have a bug to report, please let us >> know. >> >> There is one outstanding bug - breaking the Python 2.7 build on 32-bit >> Windows - that I would like to resolve before release, if anybody has >> thoughts: https://github.com/nipy/nibabel/pull/367 >> >> Thanks! >> -- >> Christopher J Markiewicz >> Ph.D. Candidate, Quantitative Neuroscience Laboratory >> Boston University >> _______________________________________________ >> Neuroimaging mailing list >> Neuroimaging at python.org >> https://mail.python.org/mailman/listinfo/neuroimaging >> > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From davmazo at gmail.com Mon Nov 9 08:54:29 2015 From: davmazo at gmail.com (David Dalmazzo) Date: Mon, 9 Nov 2015 14:54:29 +0100 Subject: [Neuroimaging] Upcoming nibabel bug fix release In-Reply-To: References: <563F5FA6.2080303@bu.edu> Message-ID: Hi Ben, Yes I'm talking with Robert that has developed Fieldtrip for Matlab but we are also stocked in some bugs. Actually my last chance is to do it extracting the data with Workbench, I will check. Thanks for the info Ben Best David On Mon, Nov 9, 2015 at 2:13 PM, Ben Cipollini wrote: > Hi David, > > CIFTI support is not complete in nibabel, so no way to do it in nibabel > yet. > > Have you tried using the conversion tools inside of Connectome Workbench? > Have you tried asking about the fieldtrip issue on the HCP email list? They > tend to be very responsive. > > Ben > > On Mon, Nov 9, 2015 at 2:48 AM, David Dalmazzo wrote: > >> Hi all, >> Sound that new python version is not totally compatible with nibabel. My >> question is, it is possible to parse Cifti files from HCP using older >> version of Python? I found very complicated to resolve this task of extract >> connectome data from those files, not even with Matlab R2015b >> (8.6.0.267246) library fieldtrip is not working properly. >> Someone has a different technique to extract connectome matrix from >> .dconn.nii files? >> Thanks >> >> David >> >> On Sun, Nov 8, 2015 at 3:43 PM, Christopher J Markiewicz > > wrote: >> >>> Hi all, >>> >>> Python 3.5, numpy 1.10, and the upcoming pydicom 1.0 are all taking the >>> opportunity to break nibabel in little ways, so it seems like a good >>> time to push out a bug-fix release (v2.0.2). >>> >>> Since 2.0.1, a lot of effort has gone into rearchitecting, and we (by >>> which I mostly mean Ben Cipollini) are plugging along toward cleanly >>> integrated Gifti and Cifti support. For simplicity, I'll be leaving that >>> work out of the current release so that all of the relevant changes can >>> be released at once. >>> >>> I'm doing the preparation work for 2.0.2 in GitHub issue 377 >>> (https://github.com/nipy/nibabel/pull/377), so I'd appreciate as many >>> eyes on it as can be spared. In particular, if there's a bug fix that >>> I've failed to include, or if you have a bug to report, please let us >>> know. >>> >>> There is one outstanding bug - breaking the Python 2.7 build on 32-bit >>> Windows - that I would like to resolve before release, if anybody has >>> thoughts: https://github.com/nipy/nibabel/pull/367 >>> >>> Thanks! >>> -- >>> Christopher J Markiewicz >>> Ph.D. Candidate, Quantitative Neuroscience Laboratory >>> Boston University >>> _______________________________________________ >>> Neuroimaging mailing list >>> Neuroimaging at python.org >>> https://mail.python.org/mailman/listinfo/neuroimaging >>> >> >> >> _______________________________________________ >> Neuroimaging mailing list >> Neuroimaging at python.org >> https://mail.python.org/mailman/listinfo/neuroimaging >> >> > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From arokem at gmail.com Tue Nov 10 12:49:12 2015 From: arokem at gmail.com (Ariel Rokem) Date: Tue, 10 Nov 2015 09:49:12 -0800 Subject: [Neuroimaging] Postdoc training at the University of Washington in neuroengineering/data science Message-ID: With apologies for cross-posting, I am posting the following on behalf of my colleague, Ione Fine: Two excellent postdoctoral fellowship opportunities with a deadline of January 15th are available at the University of Washington, Seattle, USA: http://uwin.washington.edu/post-docs/apply-post-docs/ http://escience.washington.edu/postdoctoral-fellowships Candidates with a strong computational background (e.g., machine learning, computer vision, neuroengineering, etc.) are sought to work on the following project: Prof. Fine has over several years worked in collaboration with Second Sight (developers of a retinal prosthetic, analogous to a cochlear implant, on the market). She has developed developed a model that, for any given pulse train, is pretty good at predicting what a patient implanted with a retinal prosthetic will see (essentially a linear-nonlinear model with some weird tweaks because the retina is responding to current instead of light). But what the field really needs is the *reverse* of this model ? we need to be able to predict what electrical pulses (across the set of electrodes) will produce a percept that most closely matches the percept that would normally be elicited by whatever it is the patient is looking at. It?s actually a really tricky problem for a variety of reasons. Building such a model would be of very high impact on the field, because it wouldn?t just help Second Sight patients ? it would likely be generalized by all the other groups trying to build prosthetic devices (e.g., with optogenetics). Please contact Prof. Fine (ionefine at uw.edu) if you are interested in this particular project or just want information about UWIN ( http://uwin.washington.edu/). Feel free to also contact me (arokem at gmail.com) for questions about the Data Science Environment at the University of Washington (http://escience.washington.edu/) and the eScience fellowships. -------------- next part -------------- An HTML attachment was scrubbed... URL: From matthew.brett at gmail.com Thu Nov 12 23:54:07 2015 From: matthew.brett at gmail.com (Matthew Brett) Date: Thu, 12 Nov 2015 20:54:07 -0800 Subject: [Neuroimaging] [dipy]Numpy on py2.6-32 bot In-Reply-To: References: Message-ID: Hi, On Wed, Oct 28, 2015 at 4:53 PM, Ariel Rokem wrote: > Does anyone know what version of numpy is running on this buildbot? > > http://nipy.bic.berkeley.edu/builders/dipy-py2.6-32 > > We are planning to drop support for numpy<1.7 with the upcoming release > (unless someone tells me that's crazy) and I suspect that these failures > could be because this bot hasn't gotten the memo. Sorry it took a while to check, I was in Cuba, have been snowed under since I got back. Yes, that bot is using the stock numpy for Ubuntu 12.04 which appears to be 1.6.1. I've set that bot up to install numpy as part of the build run, I hope pip's caching will make it fast enough, Cheers, Matthew From arokem at gmail.com Fri Nov 13 00:34:42 2015 From: arokem at gmail.com (Ariel Rokem) Date: Thu, 12 Nov 2015 21:34:42 -0800 Subject: [Neuroimaging] [dipy]Numpy on py2.6-32 bot In-Reply-To: References: Message-ID: On Thu, Nov 12, 2015 at 8:54 PM, Matthew Brett wrote: > Hi, > > On Wed, Oct 28, 2015 at 4:53 PM, Ariel Rokem wrote: > > Does anyone know what version of numpy is running on this buildbot? > > > > http://nipy.bic.berkeley.edu/builders/dipy-py2.6-32 > > > > We are planning to drop support for numpy<1.7 with the upcoming release > > (unless someone tells me that's crazy) and I suspect that these failures > > could be because this bot hasn't gotten the memo. > > Sorry it took a while to check, I was in Cuba, have been snowed under > since I got back. > > Yes, that bot is using the stock numpy for Ubuntu 12.04 which appears > to be 1.6.1. > > I've set that bot up to install numpy as part of the build run, I hope > pip's caching will make it fast enough, > > OK - thanks for doing that! Ariel > Cheers, > > Matthew > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From matthew.brett at gmail.com Fri Nov 13 17:02:20 2015 From: matthew.brett at gmail.com (Matthew Brett) Date: Fri, 13 Nov 2015 14:02:20 -0800 Subject: [Neuroimaging] [dipy]Numpy on py2.6-32 bot In-Reply-To: References: Message-ID: On Wed, Oct 28, 2015 at 4:56 PM, Nathaniel Smith wrote: > Useful general tip: if you put a 'pip freeze' command in your build > script, then it dumps the versions of all installed packages to stdout > and you can look at them in your build logs later. Thanks - good idea - I added that step to most builds: http://nipy.bic.berkeley.edu/builders/nibabel-py2.7-osx-10.10/builds/25/steps/shell_3/logs/stdio Cheers, Matthew From satra at mit.edu Sun Nov 15 13:39:54 2015 From: satra at mit.edu (Satrajit Ghosh) Date: Sun, 15 Nov 2015 13:39:54 -0500 Subject: [Neuroimaging] [Nipype] changing the license of Nipype from BSD to Apache 2 Message-ID: hi all, i had a question last week about Nipype's license (an area i don't understand well) and i was told that the BSD license can be restrictive in a software patenting sense. here is one post i found that describes the differences, and the legal differences have to do with software patents, something that didn't exist when the original BSD/MIT style licenses were crafted. https://www.chef.io/blog/2009/08/11/why-we-chose-the-apache-license/ i would like to ask this community for guidance on the issue or pointers to people who can provide guidance. if there doesn't seem to be any major roadblocks and apache 2 offers some advantages over BSD, i'm inclined to adopt it. the change seems quite straightforward, but before we embrace it, i would like to get a better handle. cheers, satra -------------- next part -------------- An HTML attachment was scrubbed... URL: From njs at pobox.com Sun Nov 15 13:46:25 2015 From: njs at pobox.com (Nathaniel Smith) Date: Sun, 15 Nov 2015 10:46:25 -0800 Subject: [Neuroimaging] [Nipype] changing the license of Nipype from BSD to Apache 2 In-Reply-To: References: Message-ID: Apache 2 and GPL 2 are incompatible, so you risk reducing how many people can use your code. Some projects dual license under BSD and Apache 2, because they want to offer BSD terms to the world, but they want to ask contributors to make the patent guarantees required by Apache 2. Actually making license changes generally requires tracking down every person who's ever contributed a patch and getting them to sign off on it. Maybe you don't need that for this case given the particular licenses; you'd need to check with an OSS lawyer if you wanted to try something more clever. -n On Nov 15, 2015 10:40 AM, "Satrajit Ghosh" wrote: > hi all, > > i had a question last week about Nipype's license (an area i don't > understand well) and i was told that the BSD license can be restrictive in > a software patenting sense. here is one post i found that describes the > differences, and the legal differences have to do with software patents, > something that didn't exist when the original BSD/MIT style licenses were > crafted. > > https://www.chef.io/blog/2009/08/11/why-we-chose-the-apache-license/ > > i would like to ask this community for guidance on the issue or pointers > to people who can provide guidance. > > if there doesn't seem to be any major roadblocks and apache 2 offers some > advantages over BSD, i'm inclined to adopt it. the change seems quite > straightforward, but before we embrace it, i would like to get a better > handle. > > cheers, > > satra > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From pieper at isomics.com Mon Nov 16 09:46:02 2015 From: pieper at isomics.com (Steve Pieper) Date: Mon, 16 Nov 2015 09:46:02 -0500 Subject: [Neuroimaging] [Nipype] changing the license of Nipype from BSD to Apache 2 In-Reply-To: References: Message-ID: Hi Satra - We considered a lot of issues related to patents, copyright, etc when working with Partners legal department to write the Slicer license [1] but also importantly some institutional concerns about liability where software could be used for medical purposes. It's worked well and has been used basically unchanged by several other projects, such as FreeSurfer [2]. There are a lot of details to consider if you really want to get into it. Rosen's book is a great reference [3]. We also consulted him (in person in addition to reading his book) when putting together the Slicer IP policies. I'd be happy to discuss what we considered at the time. So you could consider using a version of the Slicer license. Apache 2 might be a better choice though since it's more well known and addresses many but not all of the same issues. ITK uses it for example. HTH, Steve [1] http://slicer.org/pages/LicenseText [2] https://surfer.nmr.mgh.harvard.edu/registration.html [3] http://www.rosenlaw.com/oslbook.htm On Sun, Nov 15, 2015 at 1:46 PM, Nathaniel Smith wrote: > Apache 2 and GPL 2 are incompatible, so you risk reducing how many people > can use your code. > > Some projects dual license under BSD and Apache 2, because they want to > offer BSD terms to the world, but they want to ask contributors to make the > patent guarantees required by Apache 2. > > Actually making license changes generally requires tracking down every > person who's ever contributed a patch and getting them to sign off on it. > Maybe you don't need that for this case given the particular licenses; > you'd need to check with an OSS lawyer if you wanted to try something more > clever. > > -n > On Nov 15, 2015 10:40 AM, "Satrajit Ghosh" wrote: > >> hi all, >> >> i had a question last week about Nipype's license (an area i don't >> understand well) and i was told that the BSD license can be restrictive in >> a software patenting sense. here is one post i found that describes the >> differences, and the legal differences have to do with software patents, >> something that didn't exist when the original BSD/MIT style licenses were >> crafted. >> >> https://www.chef.io/blog/2009/08/11/why-we-chose-the-apache-license/ >> >> i would like to ask this community for guidance on the issue or pointers >> to people who can provide guidance. >> >> if there doesn't seem to be any major roadblocks and apache 2 offers some >> advantages over BSD, i'm inclined to adopt it. the change seems quite >> straightforward, but before we embrace it, i would like to get a better >> handle. >> >> cheers, >> >> satra >> >> >> _______________________________________________ >> Neuroimaging mailing list >> Neuroimaging at python.org >> https://mail.python.org/mailman/listinfo/neuroimaging >> >> > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From choldgraf at berkeley.edu Sat Nov 21 14:50:36 2015 From: choldgraf at berkeley.edu (Chris Holdgraf) Date: Sat, 21 Nov 2015 11:50:36 -0800 Subject: [Neuroimaging] Co-registering MRs to CT in python? Message-ID: Hey all - I'm in an electrocorticography lab that's trying to update the process we use for localizing electrodes on a patient's brain. Right now we get a pre-operative MRI, as well as a CT scan after electrodes have been implanted. In order to localize electrodes, we need to co-register the CT to the MRI and then define electrode locations on the CT. Right now, all the tools I've seen for this are in Matlab. They generally use either Fieldtrip (e.g., this ) or some custom code that uses SPM / FSL under the hood. I am wondering if tools like this exist in python as well, or if we're restricted to using Matlab. Obviously some steps in the pipeline might be missing (e.g., selecting electrodes in a CT scan and applying a label to them), but if the other steps are there (e.g., co-registering a CT to an MRI etc) then I may try to spend time filling in the missing holes. Anyone know of good resources along these lines? I've been playing around with nibabel for I/O and pysurface for doing surface recons of our MRIs, but haven't found a good tool for co-registration etc. Any info is appreciated (and apologies if this is a naive question). Chris -------------- next part -------------- An HTML attachment was scrubbed... URL: From rlaplant at nmr.mgh.harvard.edu Sat Nov 21 15:08:44 2015 From: rlaplant at nmr.mgh.harvard.edu (Roan LaPlante) Date: Sat, 21 Nov 2015 15:08:44 -0500 Subject: [Neuroimaging] Co-registering MRs to CT in python? In-Reply-To: References: Message-ID: Hi Chris, I spent the better part of the last year writing a program in python that does exactly this and tweaking the methods to work better. Take a look at http://github.com/aestrivex/gselu best R On Nov 21, 2015 2:51 PM, "Chris Holdgraf" wrote: > Hey all - I'm in an electrocorticography lab that's trying to update the > process we use for localizing electrodes on a patient's brain. Right now we > get a pre-operative MRI, as well as a CT scan after electrodes have been > implanted. In order to localize electrodes, we need to co-register the CT > to the MRI and then define electrode locations on the CT. > > Right now, all the tools I've seen for this are in Matlab. They generally > use either Fieldtrip (e.g., this > ) > or some custom code that uses SPM / FSL under the hood. > > I am wondering if tools like this exist in python as well, or if we're > restricted to using Matlab. Obviously some steps in the pipeline might be > missing (e.g., selecting electrodes in a CT scan and applying a label to > them), but if the other steps are there (e.g., co-registering a CT to an > MRI etc) then I may try to spend time filling in the missing holes. > > Anyone know of good resources along these lines? I've been playing around > with nibabel for I/O and pysurface for doing surface recons of our MRIs, > but haven't found a good tool for co-registration etc. > > Any info is appreciated (and apologies if this is a naive question). > > Chris > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > > The information in this e-mail is intended only for the person to whom it > is > addressed. If you believe this e-mail was sent to you in error and the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail. > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From rlaplant at nmr.mgh.harvard.edu Sat Nov 21 15:13:50 2015 From: rlaplant at nmr.mgh.harvard.edu (Roan LaPlante) Date: Sat, 21 Nov 2015 15:13:50 -0500 Subject: [Neuroimaging] Co-registering MRs to CT in python? In-Reply-To: References: Message-ID: By the way my program uses freesurfer binaries to do the coregistration (and expects files organized in a freesurfer reconstruction). All of the MR/CT methods use mutual information registration. There are python tools that implement this type of algorithm but in my experience they were much more difficult to work with. Freesurfer's mutual information registration does some rather clever resampling which was much smarter than what I was able to hack together in nipy. On Nov 21, 2015 3:08 PM, "Roan LaPlante" wrote: > Hi Chris, > > I spent the better part of the last year writing a program in python that > does exactly this and tweaking the methods to work better. > > Take a look at http://github.com/aestrivex/gselu > > best > R > On Nov 21, 2015 2:51 PM, "Chris Holdgraf" wrote: > >> Hey all - I'm in an electrocorticography lab that's trying to update the >> process we use for localizing electrodes on a patient's brain. Right now we >> get a pre-operative MRI, as well as a CT scan after electrodes have been >> implanted. In order to localize electrodes, we need to co-register the CT >> to the MRI and then define electrode locations on the CT. >> >> Right now, all the tools I've seen for this are in Matlab. They generally >> use either Fieldtrip (e.g., this >> ) >> or some custom code that uses SPM / FSL under the hood. >> >> I am wondering if tools like this exist in python as well, or if we're >> restricted to using Matlab. Obviously some steps in the pipeline might be >> missing (e.g., selecting electrodes in a CT scan and applying a label to >> them), but if the other steps are there (e.g., co-registering a CT to an >> MRI etc) then I may try to spend time filling in the missing holes. >> >> Anyone know of good resources along these lines? I've been playing around >> with nibabel for I/O and pysurface for doing surface recons of our MRIs, >> but haven't found a good tool for co-registration etc. >> >> Any info is appreciated (and apologies if this is a naive question). >> >> Chris >> >> _______________________________________________ >> Neuroimaging mailing list >> Neuroimaging at python.org >> https://mail.python.org/mailman/listinfo/neuroimaging >> >> >> The information in this e-mail is intended only for the person to whom it >> is >> addressed. If you believe this e-mail was sent to you in error and the >> e-mail >> contains patient information, please contact the Partners Compliance >> HelpLine at >> http://www.partners.org/complianceline . If the e-mail was sent to you >> in error >> but does not contain patient information, please contact the sender and >> properly >> dispose of the e-mail. >> >> -------------- next part -------------- An HTML attachment was scrubbed... URL: From arokem at gmail.com Sat Nov 21 18:14:20 2015 From: arokem at gmail.com (Ariel Rokem) Date: Sat, 21 Nov 2015 15:14:20 -0800 Subject: [Neuroimaging] Use gitter as a channel for Q&A Message-ID: Hello, We are considering (https://github.com/nipy/dipy/pull/773) whether to use Gitter as a channel for users to come and ask questions about using the software. Pros: - Give users another public channel to ask questions. This one seems to have a relatively low barrier to entry, because it feels so "casual". This is a good one in my opinion, because I suspect that many users facing a difficulty early on in their use of the software might meet some small technical issues (e.g. in installing) that would be very easy to debug in a quick informal conversation over a chat. Cons: - Messages are not archived in a google-able manner. Discussions are sometimes hard to follow and follow up on. People have to be logged on to get the messages. - We are also using gitter as a channel to chat about development. This might confuse some users. I think this is actually also a pro - some users might feel compelled to get involved in discussions about development, and in the work of development. In general, I agree with arguments Matthew has made in the past that separating "users" from "developers" too firmly can be counter-productive to a community that aims to empower users of computation in science. At the moment, I really just think of starting a little experiment of offering this as a channel for help, including putting a side-car chat window on the dipy website. I might be missing a few pros and cons. What do you all think? Ariel -------------- next part -------------- An HTML attachment was scrubbed... URL: From arokem at gmail.com Sun Nov 22 10:38:07 2015 From: arokem at gmail.com (Ariel Rokem) Date: Sun, 22 Nov 2015 07:38:07 -0800 Subject: [Neuroimaging] Co-registering MRs to CT in python? In-Reply-To: References: Message-ID: Hi Chris, I don't know that they've been used for this purpose before, but you might want to try some of the tools for registration that are in dipy: http://nipy.org/dipy/examples_built/syn_registration_3d.html#example-syn-registration-3d Cheers, Ariel On Sat, Nov 21, 2015 at 11:50 AM, Chris Holdgraf wrote: > Hey all - I'm in an electrocorticography lab that's trying to update the > process we use for localizing electrodes on a patient's brain. Right now we > get a pre-operative MRI, as well as a CT scan after electrodes have been > implanted. In order to localize electrodes, we need to co-register the CT > to the MRI and then define electrode locations on the CT. > > Right now, all the tools I've seen for this are in Matlab. They generally > use either Fieldtrip (e.g., this > ) > or some custom code that uses SPM / FSL under the hood. > > I am wondering if tools like this exist in python as well, or if we're > restricted to using Matlab. Obviously some steps in the pipeline might be > missing (e.g., selecting electrodes in a CT scan and applying a label to > them), but if the other steps are there (e.g., co-registering a CT to an > MRI etc) then I may try to spend time filling in the missing holes. > > Anyone know of good resources along these lines? I've been playing around > with nibabel for I/O and pysurface for doing surface recons of our MRIs, > but haven't found a good tool for co-registration etc. > > Any info is appreciated (and apologies if this is a naive question). > > Chris > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From garyfallidis at gmail.com Sun Nov 22 10:51:46 2015 From: garyfallidis at gmail.com (Eleftherios Garyfallidis) Date: Sun, 22 Nov 2015 10:51:46 -0500 Subject: [Neuroimaging] Co-registering MRs to CT in python? In-Reply-To: References: Message-ID: And this is the tutorial for the affine registration. You will need the development version to use this one. https://github.com/nipy/dipy/blob/master/doc/examples/affine_registration_3d.py -------------- next part -------------- An HTML attachment was scrubbed... URL: From choldgraf at berkeley.edu Sun Nov 22 17:04:22 2015 From: choldgraf at berkeley.edu (Chris Holdgraf) Date: Sun, 22 Nov 2015 14:04:22 -0800 Subject: [Neuroimaging] Neuroimaging Digest, Vol 6, Issue 10 In-Reply-To: References: Message-ID: Hey Roan - sorry for the slow response, I have this listserv on a digest, so I'm going to go ahead and give my +1 on using gitter as well :) That looks like a really useful package. However I can't find documentation (e.g., readme, tutorial, etc). Does it exist somewhere? I'd love to give this a shot and contribute if it's useful. Chris -------------- next part -------------- An HTML attachment was scrubbed... URL: From rlaplant at nmr.mgh.harvard.edu Sun Nov 22 18:36:30 2015 From: rlaplant at nmr.mgh.harvard.edu (Roan LaPlante) Date: Sun, 22 Nov 2015 18:36:30 -0500 Subject: [Neuroimaging] Neuroimaging Digest, Vol 6, Issue 10 In-Reply-To: References: Message-ID: On Nov 22, 2015 6:35 PM, "Roan LaPlante" wrote: > > There is some documentation (not completely current but still extensive) on the github wiki page > > github.com/aestrivex/gselu/wiki > On Nov 22, 2015 5:05 PM, "Chris Holdgraf" wrote: >> >> Hey Roan - sorry for the slow response, I have this listserv on a digest, so I'm going to go ahead and give my +1 on using gitter as well :) >> >> That looks like a really useful package. However I can't find documentation (e.g., readme, tutorial, etc). Does it exist somewhere? I'd love to give this a shot and contribute if it's useful. >> >> Chris >> >> _______________________________________________ >> Neuroimaging mailing list >> Neuroimaging at python.org >> https://mail.python.org/mailman/listinfo/neuroimaging >> >> >> The information in this e-mail is intended only for the person to whom it is >> addressed. If you believe this e-mail was sent to you in error and the e-mail >> contains patient information, please contact the Partners Compliance HelpLine at >> http://www.partners.org/complianceline . If the e-mail was sent to you in error >> but does not contain patient information, please contact the sender and properly >> dispose of the e-mail. >> -------------- next part -------------- An HTML attachment was scrubbed... URL: From effigies at bu.edu Mon Nov 23 17:09:08 2015 From: effigies at bu.edu (Christopher J Markiewicz) Date: Mon, 23 Nov 2015 17:09:08 -0500 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release Message-ID: <56538E84.6000805@bu.edu> Hi all, I just pushed a 2.0.2 bugfix release for nibabel. This release includes a number of fixes to ensure nibabel works as expected for users running Python 3.5 and numpy 1.10. Here is the Changelog: * 2.0.2 (Monday 23 November 2015) * Fix for integer overflow on large images (pr/325) (MB); * Fix for Freesurfer nifti files with unusual dimensions (pr/332) (Chris Markiewicz); * Fix typos on benchmarks and tests (pr/336, pr/340, pr/347) (Chris Markiewicz); * Fix Windows install script (pr/339) (MB); * Support for Python 3.5 (pr/363) (MB) and numpy 1.10 (pr/358) (Chris Markiewicz); * Update pydicom imports to permit version 1.0 (pr/379) (Chris Markiewicz); * Workaround for Python 3.5.0 gzip regression (pr/383) (Ben Cipollini). * tripwire.TripWire object now raises subclass of AttributeError when trying to get an attribute, rather than a direct subclass of Exception. This prevents Python 3.5 triggering the tripwire when doing inspection prior to running doctests. * Minor API change for tripwire.TripWire object; code that checked for AttributeError will now also catch TripWireError. Thanks very much to all involved. Please let us know if you have any problems. -- Christopher J Markiewicz From gael.varoquaux at normalesup.org Mon Nov 23 17:53:12 2015 From: gael.varoquaux at normalesup.org (Gael Varoquaux) Date: Mon, 23 Nov 2015 23:53:12 +0100 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: <56538E84.6000805@bu.edu> References: <56538E84.6000805@bu.edu> Message-ID: <20151123225312.GK2776852@phare.normalesup.org> Thanks Chris, this is super useful! Ga?l On Mon, Nov 23, 2015 at 05:09:08PM -0500, Christopher J Markiewicz wrote: > Hi all, > I just pushed a 2.0.2 bugfix release for nibabel. This release includes > a number of fixes to ensure nibabel works as expected for users running > Python 3.5 and numpy 1.10. > Here is the Changelog: > * 2.0.2 (Monday 23 November 2015) > * Fix for integer overflow on large images (pr/325) (MB); > * Fix for Freesurfer nifti files with unusual dimensions (pr/332) > (Chris Markiewicz); > * Fix typos on benchmarks and tests (pr/336, pr/340, pr/347) (Chris > Markiewicz); > * Fix Windows install script (pr/339) (MB); > * Support for Python 3.5 (pr/363) (MB) and numpy 1.10 (pr/358) (Chris > Markiewicz); > * Update pydicom imports to permit version 1.0 (pr/379) (Chris > Markiewicz); > * Workaround for Python 3.5.0 gzip regression (pr/383) (Ben > Cipollini). > * tripwire.TripWire object now raises subclass of AttributeError when > trying to get an attribute, rather than a direct subclass of > Exception. This prevents Python 3.5 triggering the tripwire when > doing inspection prior to running doctests. > * Minor API change for tripwire.TripWire object; code that checked for > AttributeError will now also catch TripWireError. > Thanks very much to all involved. Please let us know if you have any > problems. -- Gael Varoquaux Researcher, INRIA Parietal NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France Phone: ++ 33-1-69-08-79-68 http://gael-varoquaux.info http://twitter.com/GaelVaroquaux From satra at mit.edu Mon Nov 23 17:56:46 2015 From: satra at mit.edu (Satrajit Ghosh) Date: Mon, 23 Nov 2015 17:56:46 -0500 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: <20151123225312.GK2776852@phare.normalesup.org> References: <56538E84.6000805@bu.edu> <20151123225312.GK2776852@phare.normalesup.org> Message-ID: thanks chris. On Mon, Nov 23, 2015 at 5:53 PM, Gael Varoquaux < gael.varoquaux at normalesup.org> wrote: > Thanks Chris, this is super useful! > > Ga?l > > On Mon, Nov 23, 2015 at 05:09:08PM -0500, Christopher J Markiewicz wrote: > > Hi all, > > > I just pushed a 2.0.2 bugfix release for nibabel. This release includes > > a number of fixes to ensure nibabel works as expected for users running > > Python 3.5 and numpy 1.10. > > > Here is the Changelog: > > > * 2.0.2 (Monday 23 November 2015) > > > * Fix for integer overflow on large images (pr/325) (MB); > > * Fix for Freesurfer nifti files with unusual dimensions (pr/332) > > (Chris Markiewicz); > > * Fix typos on benchmarks and tests (pr/336, pr/340, pr/347) (Chris > > Markiewicz); > > * Fix Windows install script (pr/339) (MB); > > * Support for Python 3.5 (pr/363) (MB) and numpy 1.10 (pr/358) (Chris > > Markiewicz); > > * Update pydicom imports to permit version 1.0 (pr/379) (Chris > > Markiewicz); > > * Workaround for Python 3.5.0 gzip regression (pr/383) (Ben > > Cipollini). > > * tripwire.TripWire object now raises subclass of AttributeError when > > trying to get an attribute, rather than a direct subclass of > > Exception. This prevents Python 3.5 triggering the tripwire when > > doing inspection prior to running doctests. > > * Minor API change for tripwire.TripWire object; code that checked for > > AttributeError will now also catch TripWireError. > > > Thanks very much to all involved. Please let us know if you have any > > problems. > -- > Gael Varoquaux > Researcher, INRIA Parietal > NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France > Phone: ++ 33-1-69-08-79-68 > http://gael-varoquaux.info http://twitter.com/GaelVaroquaux > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From matthew.brett at gmail.com Mon Nov 23 19:51:12 2015 From: matthew.brett at gmail.com (Matthew Brett) Date: Mon, 23 Nov 2015 16:51:12 -0800 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: <56538E84.6000805@bu.edu> References: <56538E84.6000805@bu.edu> Message-ID: On Mon, Nov 23, 2015 at 2:09 PM, Christopher J Markiewicz wrote: > Hi all, > > I just pushed a 2.0.2 bugfix release for nibabel. This release includes > a number of fixes to ensure nibabel works as expected for users running > Python 3.5 and numpy 1.10. > > Here is the Changelog: > > * 2.0.2 (Monday 23 November 2015) > > * Fix for integer overflow on large images (pr/325) (MB); > * Fix for Freesurfer nifti files with unusual dimensions (pr/332) > (Chris Markiewicz); > * Fix typos on benchmarks and tests (pr/336, pr/340, pr/347) (Chris > Markiewicz); > * Fix Windows install script (pr/339) (MB); > * Support for Python 3.5 (pr/363) (MB) and numpy 1.10 (pr/358) (Chris > Markiewicz); > * Update pydicom imports to permit version 1.0 (pr/379) (Chris > Markiewicz); > * Workaround for Python 3.5.0 gzip regression (pr/383) (Ben > Cipollini). > * tripwire.TripWire object now raises subclass of AttributeError when > trying to get an attribute, rather than a direct subclass of > Exception. This prevents Python 3.5 triggering the tripwire when > doing inspection prior to running doctests. > * Minor API change for tripwire.TripWire object; code that checked for > AttributeError will now also catch TripWireError. > > Thanks very much to all involved. Please let us know if you have any > problems. Great job - thanks very much for taking this on, Cheers, Matthew From bertrand.thirion at inria.fr Tue Nov 24 02:54:55 2015 From: bertrand.thirion at inria.fr (Bertrand Thirion) Date: Tue, 24 Nov 2015 08:54:55 +0100 (CET) Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: <56538E84.6000805@bu.edu> References: <56538E84.6000805@bu.edu> Message-ID: <1551104635.21625371.1448351695456.JavaMail.zimbra@inria.fr> Many thanks for all these contributions ! Best, Bertrand ----- Mail original ----- > De: "Christopher J Markiewicz" > ?: "Neuroimaging analysis in Python" > Envoy?: Lundi 23 Novembre 2015 23:09:08 > Objet: [Neuroimaging] Nibabel 2.0.2 bugfix release > > Hi all, > > I just pushed a 2.0.2 bugfix release for nibabel. This release includes > a number of fixes to ensure nibabel works as expected for users running > Python 3.5 and numpy 1.10. > > Here is the Changelog: > > * 2.0.2 (Monday 23 November 2015) > > * Fix for integer overflow on large images (pr/325) (MB); > * Fix for Freesurfer nifti files with unusual dimensions (pr/332) > (Chris Markiewicz); > * Fix typos on benchmarks and tests (pr/336, pr/340, pr/347) (Chris > Markiewicz); > * Fix Windows install script (pr/339) (MB); > * Support for Python 3.5 (pr/363) (MB) and numpy 1.10 (pr/358) (Chris > Markiewicz); > * Update pydicom imports to permit version 1.0 (pr/379) (Chris > Markiewicz); > * Workaround for Python 3.5.0 gzip regression (pr/383) (Ben > Cipollini). > * tripwire.TripWire object now raises subclass of AttributeError when > trying to get an attribute, rather than a direct subclass of > Exception. This prevents Python 3.5 triggering the tripwire when > doing inspection prior to running doctests. > * Minor API change for tripwire.TripWire object; code that checked for > AttributeError will now also catch TripWireError. > > Thanks very much to all involved. Please let us know if you have any > problems. > > -- > Christopher J Markiewicz > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > From bcipolli at ucsd.edu Tue Nov 24 06:58:20 2015 From: bcipolli at ucsd.edu (Ben Cipollini) Date: Tue, 24 Nov 2015 06:58:20 -0500 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: <1551104635.21625371.1448351695456.JavaMail.zimbra@inria.fr> References: <56538E84.6000805@bu.edu> <1551104635.21625371.1448351695456.JavaMail.zimbra@inria.fr> Message-ID: I know how much work @Chris put into this--and into lots of pull requests and code reviews that weren't included here--so huge thanks to him. And of course, thanks to Matthew Brett for the wide-ranging contribution he makes to nibabel and the nipy community. Cool stuff y'all! On Tue, Nov 24, 2015 at 2:54 AM, Bertrand Thirion wrote: > Many thanks for all these contributions ! > Best, > > Bertrand > > ----- Mail original ----- > > De: "Christopher J Markiewicz" > > ?: "Neuroimaging analysis in Python" > > Envoy?: Lundi 23 Novembre 2015 23:09:08 > > Objet: [Neuroimaging] Nibabel 2.0.2 bugfix release > > > > Hi all, > > > > I just pushed a 2.0.2 bugfix release for nibabel. This release includes > > a number of fixes to ensure nibabel works as expected for users running > > Python 3.5 and numpy 1.10. > > > > Here is the Changelog: > > > > * 2.0.2 (Monday 23 November 2015) > > > > * Fix for integer overflow on large images (pr/325) (MB); > > * Fix for Freesurfer nifti files with unusual dimensions (pr/332) > > (Chris Markiewicz); > > * Fix typos on benchmarks and tests (pr/336, pr/340, pr/347) (Chris > > Markiewicz); > > * Fix Windows install script (pr/339) (MB); > > * Support for Python 3.5 (pr/363) (MB) and numpy 1.10 (pr/358) (Chris > > Markiewicz); > > * Update pydicom imports to permit version 1.0 (pr/379) (Chris > > Markiewicz); > > * Workaround for Python 3.5.0 gzip regression (pr/383) (Ben > > Cipollini). > > * tripwire.TripWire object now raises subclass of AttributeError when > > trying to get an attribute, rather than a direct subclass of > > Exception. This prevents Python 3.5 triggering the tripwire when > > doing inspection prior to running doctests. > > * Minor API change for tripwire.TripWire object; code that checked for > > AttributeError will now also catch TripWireError. > > > > Thanks very much to all involved. Please let us know if you have any > > problems. > > > > -- > > Christopher J Markiewicz > > _______________________________________________ > > Neuroimaging mailing list > > Neuroimaging at python.org > > https://mail.python.org/mailman/listinfo/neuroimaging > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From lists at onerussian.com Tue Nov 24 08:50:17 2015 From: lists at onerussian.com (Yaroslav Halchenko) Date: Tue, 24 Nov 2015 08:50:17 -0500 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: References: <56538E84.6000805@bu.edu> <1551104635.21625371.1448351695456.JavaMail.zimbra@inria.fr> Message-ID: <20151124135017.GP7844@onerussian.com> On Tue, 24 Nov 2015, Ben Cipollini wrote: > I know how much work @Chris put into this--and into lots of pull requests and > code reviews that weren't included here--so huge thanks to him.? > And of course, thanks to Matthew Brett for the wide-ranging contribution he > makes to nibabel and the nipy community. Big kudos to Chris, Matthew and every contributor to nibabel. > Cool stuff y'all! +100 ;) FWIW -- 2.0.2 was uploaded now through out all releases within NeuroDebian and Debian proper unstable. Cheers! -- Yaroslav O. Halchenko Center for Open Neuroscience http://centerforopenneuroscience.org Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik From garyfallidis at gmail.com Tue Nov 24 09:48:11 2015 From: garyfallidis at gmail.com (Eleftherios Garyfallidis) Date: Tue, 24 Nov 2015 09:48:11 -0500 Subject: [Neuroimaging] Nibabel 2.0.2 bugfix release In-Reply-To: <20151124135017.GP7844@onerussian.com> References: <56538E84.6000805@bu.edu> <1551104635.21625371.1448351695456.JavaMail.zimbra@inria.fr> <20151124135017.GP7844@onerussian.com> Message-ID: Well done guys! Thx much! :D On Tue, Nov 24, 2015 at 8:50 AM, Yaroslav Halchenko wrote: > > On Tue, 24 Nov 2015, Ben Cipollini wrote: > > > I know how much work @Chris put into this--and into lots of pull > requests and > > code reviews that weren't included here--so huge thanks to him. > > > And of course, thanks to Matthew Brett for the wide-ranging contribution > he > > makes to nibabel and the nipy community. > > Big kudos to Chris, Matthew and every contributor to nibabel. > > > Cool stuff y'all! > > +100 ;) > > FWIW -- 2.0.2 was uploaded now through out all releases within > NeuroDebian and Debian proper unstable. > > Cheers! > -- > Yaroslav O. Halchenko > Center for Open Neuroscience http://centerforopenneuroscience.org > Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 > Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 > WWW: http://www.linkedin.com/in/yarik > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Reid.Robert at mayo.edu Tue Nov 24 09:38:17 2015 From: Reid.Robert at mayo.edu (Reid, Robert I. (Rob)) Date: Tue, 24 Nov 2015 14:38:17 +0000 Subject: [Neuroimaging] [Dipy] Should we resample dMRI to T1w, or T1w to dMRI? Message-ID: Hi, My apologies if you've already seen this on the FSL mailing list - I'm trying to get a wide sample. We are trying to decide on whether our lab's internal diffusion MRI processing should write its images in dMRI space or T1w space, and would appreciate your opinions. The question is prompted by the EPI undistortion step, which necessarily introduces a resampling step of some sort, and tends to produce results in either T1w space (e.g. BrainSuite) or in DTI-sized voxels (e.g. FSL's topup). Which algorithm we use depends on what other data we have (topup works best when pairs of images with flipped phase encodings are available, but usually they are not), but we would like to settle on a consistent format, and avoid resampling more times than necessary for our typical analyses. Theoretically each additional resampling step introduces some degradation, so "native" space is the right one for dMRI. However, * The T1w voxels are so much smaller than the diffusion voxels that the resampling of dMRI into T1w space is typically excellent. If a diffusion processing step is using T1w (for example, tractography often uses the T1w gray/white boundary to place seeds), it seems like the T1w image would be more damaged by going to DTI than the DTI would be damaged by going to T1w. * The undistorted diffusion images *are* resampled, so they are not really in native space. If resampling is necessary it is better to resample finely (i.e. use T1w space). On the other hand, many parts of the brain, like the parietal lobe and motor-sensory strip, are relatively unaffected by EPI distortion and may be left in nearly native space after undistortion with topup, if head motion and eddy current distortion are not a large problem. Based on feedback I've already received, I should add that we will be doing quality control on the T1w <-> dMRI registration, and would fix, reject, or if necessary work around drastic registration failures. We look forward to hearing from you, Rob -- Robert I. Reid, Ph.D. | Sr. Analyst/Programmer, Information Technology Aging and Dementia Imaging Research | Opus Center for Advanced Imaging Research Mayo Clinic | 200 First Street SW | Rochester, MN 55905 | mayoclinic.org From garyfallidis at gmail.com Tue Nov 24 11:47:49 2015 From: garyfallidis at gmail.com (Eleftherios Garyfallidis) Date: Tue, 24 Nov 2015 11:47:49 -0500 Subject: [Neuroimaging] [Dipy] Should we resample dMRI to T1w, or T1w to dMRI? In-Reply-To: References: Message-ID: Hi Robert, Great question. What I personally prefer doing is first reslice the DWIs to 1mm^3 and then bring the T1 to diffusion resliced 1mm^3 space . In that way your T1 is not going to be damaged from low voxel resolution. Also you don't need to re-orient your b-vectors as no rotations were introduced. Of course there is some equivalence between going to a resampled dMRI and going to T1. This is a question I think more about which modality will be more capable in the future. I think that DWIs because they are 4D data even if their initial voxel resolution maybe lower than the T1 after being "smartly" denoised they can reach the resolution of T1 or even surpass it. Also it has been recently shown that you can create T1 looking images directly from dMRI datasets. So, it is very likely that gathering a T1 in the future may not be as important as it is today. Also, I further think that registration of dMRI datasets can use more information to correctly register different subjects because you can additionally use local orientations etc. Nonetheless, whatever you decide it is not the end of the world you can always go forth and back from the two spaces. But make sure your DWIs are resliced to 1mm^3 this helps both with registration but also with tracking. I hope this was helpful. Best regards, Eleftherios On Tue, Nov 24, 2015 at 9:38 AM, Reid, Robert I. (Rob) wrote: > Hi, > > My apologies if you've already seen this on the FSL mailing list - I'm > trying to get a wide sample. > > We are trying to decide on whether our lab's internal diffusion MRI > processing should write its images in dMRI space or T1w space, and would > appreciate your opinions. The question is prompted by the EPI undistortion > step, which necessarily introduces a resampling step of some sort, and > tends to produce results in either T1w space (e.g. BrainSuite) or in > DTI-sized voxels (e.g. FSL's topup). Which algorithm we use depends on > what other data we have (topup works best when pairs of images with flipped > phase encodings are available, but usually they are not), but we would like > to settle on a consistent format, and avoid resampling more times than > necessary for our typical analyses. > > Theoretically each additional resampling step introduces some degradation, > so "native" space is the right one for dMRI. > However, > * The T1w voxels are so much smaller than the diffusion voxels that the > resampling of dMRI into T1w space is typically excellent. If a diffusion > processing step is using T1w (for example, tractography often uses the T1w > gray/white boundary to place seeds), it seems like the T1w image would be > more damaged by going to DTI than the DTI would be damaged by going to T1w. > * The undistorted diffusion images *are* resampled, so they are not really > in native space. If resampling is necessary it is better to resample > finely (i.e. use T1w space). On the other hand, many parts of the brain, > like the parietal lobe and motor-sensory strip, are relatively unaffected > by EPI distortion and may be left in nearly native space after undistortion > with topup, if head motion and eddy current distortion are not a large > problem. > > Based on feedback I've already received, I should add that we will be > doing quality control on the T1w <-> dMRI registration, and would fix, > reject, or if necessary work around drastic registration failures. > > We look forward to hearing from you, > > Rob > > -- > Robert I. Reid, Ph.D. | Sr. Analyst/Programmer, Information Technology > Aging and Dementia Imaging Research | Opus Center for Advanced Imaging > Research > Mayo Clinic | 200 First Street SW | Rochester, MN 55905 | mayoclinic.org > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From sulantha.s at gmail.com Tue Nov 24 17:27:39 2015 From: sulantha.s at gmail.com (Sulantha Sanjeewa) Date: Tue, 24 Nov 2015 17:27:39 -0500 Subject: [Neuroimaging] Performing voxel wise logistic regression Message-ID: <9AE7A208-DDA3-457C-93D6-A2EF230974C2@gmail.com> Hello all, I would like to know whether it is possible to perform voxel wise logistic regression with two volumetric regressors (with an interaction term) using Nipy. Model: C ~ A + B + A*B Where, C is either 1 or 0, A and B both volumetric data. Thank you very much. -------------- next part -------------- An HTML attachment was scrubbed... URL: From bertrand.thirion at inria.fr Tue Nov 24 17:38:26 2015 From: bertrand.thirion at inria.fr (bthirion) Date: Tue, 24 Nov 2015 23:38:26 +0100 Subject: [Neuroimaging] Performing voxel wise logistic regression In-Reply-To: <9AE7A208-DDA3-457C-93D6-A2EF230974C2@gmail.com> References: <9AE7A208-DDA3-457C-93D6-A2EF230974C2@gmail.com> Message-ID: <5654E6E2.4090708@inria.fr> Dear Sulantha, I'm not sure I understand your question: do you mean that C is a (categorical) scalar value (e.g. disease status of the patient or some task index), or C is also a volume ? I guess that C is a scalar, and that you're in fact running some kind of multivariate analysis. You may want to take a look at the following example: nilearn.github.io/auto_examples/decoding/plot_haxby_anova_svm.html#example-decoding-plot-haxby-anova-svm-py (just replace the SVM with a logistic regression). Regarding the interaction term, we don't have implementation for that AFAIK, but this is really straightforward to do with numpy pointwise mulitplication of arrays after applying the NiftiMasker. Best, Bertrand On 24/11/2015 23:27, Sulantha Sanjeewa wrote: > Hello all, > I would like to know whether it is possible to perform voxel wise > logistic regression with two volumetric regressors (with an > interaction term) using Nipy. > Model: > C ~ A + B + A*B > Where, C is either 1 or 0, > A and B both volumetric data. > Thank you very much. > > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging -------------- next part -------------- An HTML attachment was scrubbed... URL: From sulantha.s at gmail.com Tue Nov 24 17:43:32 2015 From: sulantha.s at gmail.com (Sulantha Sanjeewa) Date: Tue, 24 Nov 2015 17:43:32 -0500 Subject: [Neuroimaging] Performing voxel wise logistic regression In-Reply-To: <5654E6E2.4090708@inria.fr> References: <9AE7A208-DDA3-457C-93D6-A2EF230974C2@gmail.com> <5654E6E2.4090708@inria.fr> Message-ID: <3A06062C-F46B-44AA-84AE-A6F8360E9F8B@gmail.com> Hi, C is a categorial variable. I think logistic regression is what I am looking for. Thank you very much. Best, S. > On Nov 24, 2015, at 5:38 PM, bthirion wrote: > > Dear Sulantha, > > I'm not sure I understand your question: do you mean that C is a (categorical) scalar value (e.g. disease status of the patient or some task index), or C is also a volume ? > I guess that C is a scalar, and that you're in fact running some kind of multivariate analysis. You may want to take a look at the following example: nilearn.github.io/auto_examples/decoding/plot_haxby_anova_svm.html#example-decoding-plot-haxby-anova-svm-py (just replace the SVM with a logistic regression). > > Regarding the interaction term, we don't have implementation for that AFAIK, but this is really straightforward to do with numpy pointwise mulitplication of arrays after applying the NiftiMasker. > > Best, > > Bertrand > > On 24/11/2015 23:27, Sulantha Sanjeewa wrote: >> Hello all, >> I would like to know whether it is possible to perform voxel wise logistic regression with two volumetric regressors (with an interaction term) using Nipy. >> Model: >> C ~ A + B + A*B >> Where, C is either 1 or 0, >> A and B both volumetric data. >> Thank you very much. >> >> >> >> _______________________________________________ >> Neuroimaging mailing list >> Neuroimaging at python.org >> https://mail.python.org/mailman/listinfo/neuroimaging > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging -------------- next part -------------- An HTML attachment was scrubbed... URL: From bcipolli at ucsd.edu Wed Nov 25 10:01:18 2015 From: bcipolli at ucsd.edu (Ben Cipollini) Date: Wed, 25 Nov 2015 10:01:18 -0500 Subject: [Neuroimaging] Use gitter as a channel for Q&A In-Reply-To: References: Message-ID: Gitter also requires a Github account. Since no tool does what we want, perhaps we could write a simple page that, for any nipy project: - Embeds Gitter chat (e.g. https://sidecar.gitter.im/) - Shows neurostars results, filtered for that component. - Easily post a message to Neurostars and/or the email list. Does this make sense? Ben On Sat, Nov 21, 2015 at 6:14 PM, Ariel Rokem wrote: > Hello, > > We are considering (https://github.com/nipy/dipy/pull/773) whether to use > Gitter as a channel for users to come and ask questions about using the > software. > > Pros: > - Give users another public channel to ask questions. This one seems to > have a relatively low barrier to entry, because it feels so "casual". This > is a good one in my opinion, because I suspect that many users facing a > difficulty early on in their use of the software might meet some small > technical issues (e.g. in installing) that would be very easy to debug in a > quick informal conversation over a chat. > > Cons: > - Messages are not archived in a google-able manner. Discussions are > sometimes hard to follow and follow up on. People have to be logged on to > get the messages. > > - We are also using gitter as a channel to chat about development. This > might confuse some users. I think this is actually also a pro - some users > might feel compelled to get involved in discussions about development, and > in the work of development. In general, I agree with arguments Matthew has > made in the past that separating "users" from "developers" too firmly can > be counter-productive to a community that aims to empower users of > computation in science. > > At the moment, I really just think of starting a little experiment of > offering this as a channel for help, including putting a side-car chat > window on the dipy website. > > I might be missing a few pros and cons. What do you all think? > > Ariel > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From gael.varoquaux at normalesup.org Wed Nov 25 10:04:17 2015 From: gael.varoquaux at normalesup.org (Gael Varoquaux) Date: Wed, 25 Nov 2015 16:04:17 +0100 Subject: [Neuroimaging] Use gitter as a channel for Q&A In-Reply-To: References: Message-ID: <20151125150417.GN971906@phare.normalesup.org> > Since no tool does what we want, perhaps we could write a simple page > that, for any nipy project: > ? Embeds Gitter chat (e.g. https://sidecar.gitter.im/) I would like to avoid gitter for nilearn. gitter (like any other chat) is very short lived, and really bad for attention issues (constant interruption). > ? Shows neurostars results, filtered for that component. > ? Easily post a message to Neurostars and/or the email list. +1 on these two. From TJiang at kesslerfoundation.org Wed Nov 18 12:38:47 2015 From: TJiang at kesslerfoundation.org (Tony Jiang) Date: Wed, 18 Nov 2015 17:38:47 +0000 Subject: [Neuroimaging] [DIPY] Comparing DIPY tensor fitting and other tools Message-ID: Dear All, A quick question about the fa maps created by DIPY (tensor model). I have a 64 direction DWI dataset and I processed this data using Diffusion Toolkit(DTK), FSL Diffusion toolbox (FDT) and DIPY. I used same gradient information and same masks for each tool. FDT and DTIK give me identical maps (except slight difference when these two apply the mask. I see some voxels having FA>1 on FDT result). DIPY gives a map very similar FA map compared to the other two FA maps I have. Shouldn?t I get an exactly same map (within rounding error maybe). Anyone has similar experience? I have attached the screenshot showing the values read from 3 different FA maps. The three maps do seem similar overall. Any inputs? Thanks, Tony [cid:894C9E85-3899-4E1F-BC75-380F4EB56A4B] The information in this transmission is intended for official use of the Kessler Foundation. It is intended for the exclusive use of the persons or entities to which it is addressed. If you are not an intended recipient or the employee or agent responsible for delivering this transmission to an intended recipient, be aware that any disclosure, dissemination, distribution or copying of this communication, or the use of its contents, is strictly prohibited. If you received this transmission in error, please notify the sender by return e-mail and delete the material from any computer. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Screen Shot 2015-11-18 at 12.26.22 PM[4].png Type: image/png Size: 859030 bytes Desc: Screen Shot 2015-11-18 at 12.26.22 PM[4].png URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Screen Shot 2015-11-18 at 12.26.22 PM.png Type: image/png Size: 859560 bytes Desc: Screen Shot 2015-11-18 at 12.26.22 PM.png URL: From paulo at mint-labs.com Tue Nov 24 12:03:49 2015 From: paulo at mint-labs.com (Paulo Mint Labs) Date: Tue, 24 Nov 2015 18:03:49 +0100 Subject: [Neuroimaging] [Dipy] Should we resample dMRI to T1w, or T1w to dMRI? In-Reply-To: References: Message-ID: Hi Rob, Normally we prefer to do everything on the dMRI space: intuitively it's 'better' (less noisy) to register a scalar image into the complex dMRI, than the other way around and have to interpolate the dMRI. What we typically do however is to resample everything to 2mm isometric, so normally the T1 goes more coarse, and the diffusion gets a bit finer resolution. And anyways, we always like to generate QA screenshot reports to quickly check all went well. Cheers! Paulo ~ *Paulo Rodrigues, PhD* *CEO & co-founder* Arc de Sant Silvestre 4, entresuelo segunda 08003 Barcelona, Spain Tel. +34 933 282 007 Mob. +34 633 817 514 paulo at mint-labs.com www.mint-labs.com *Join Mint Labs with our crowdfunding for equity campaign: HERE * Latest Press: Wall Street Journal , MIT Technology Review On Tue, Nov 24, 2015 at 3:38 PM, Reid, Robert I. (Rob) wrote: > Hi, > > My apologies if you've already seen this on the FSL mailing list - I'm > trying to get a wide sample. > > We are trying to decide on whether our lab's internal diffusion MRI > processing should write its images in dMRI space or T1w space, and would > appreciate your opinions. The question is prompted by the EPI undistortion > step, which necessarily introduces a resampling step of some sort, and > tends to produce results in either T1w space (e.g. BrainSuite) or in > DTI-sized voxels (e.g. FSL's topup). Which algorithm we use depends on > what other data we have (topup works best when pairs of images with flipped > phase encodings are available, but usually they are not), but we would like > to settle on a consistent format, and avoid resampling more times than > necessary for our typical analyses. > > Theoretically each additional resampling step introduces some degradation, > so "native" space is the right one for dMRI. > However, > * The T1w voxels are so much smaller than the diffusion voxels that the > resampling of dMRI into T1w space is typically excellent. If a diffusion > processing step is using T1w (for example, tractography often uses the T1w > gray/white boundary to place seeds), it seems like the T1w image would be > more damaged by going to DTI than the DTI would be damaged by going to T1w. > * The undistorted diffusion images *are* resampled, so they are not really > in native space. If resampling is necessary it is better to resample > finely (i.e. use T1w space). On the other hand, many parts of the brain, > like the parietal lobe and motor-sensory strip, are relatively unaffected > by EPI distortion and may be left in nearly native space after undistortion > with topup, if head motion and eddy current distortion are not a large > problem. > > Based on feedback I've already received, I should add that we will be > doing quality control on the T1w <-> dMRI registration, and would fix, > reject, or if necessary work around drastic registration failures. > > We look forward to hearing from you, > > Rob > > -- > Robert I. Reid, Ph.D. | Sr. Analyst/Programmer, Information Technology > Aging and Dementia Imaging Research | Opus Center for Advanced Imaging > Research > Mayo Clinic | 200 First Street SW | Rochester, MN 55905 | mayoclinic.org > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > -------------- next part -------------- An HTML attachment was scrubbed... URL: From 460782483 at qq.com Thu Nov 26 08:55:06 2015 From: 460782483 at qq.com (=?gb18030?B?xL7Ntw==?=) Date: Thu, 26 Nov 2015 21:55:06 +0800 Subject: [Neuroimaging] Help-"Unable to find vcvarsall.bat" Message-ID: Excuse me. I want to install Dipy in Win7. But there is a problem, when I use your installation and do this : like the installation said: I get an error saying "Unable to find vcvarsall.bat". But I do not know this mean: there ara to files named "pydistutils.cfg" and "distutils.cfg",I have tried "pydistutils.cfg", "distutils.cfg", or both...But not success? I really need you help, please! -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 248809D3 at 6009DD10.3A0F5756.jpg Type: image/jpeg Size: 64411 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: A3234A13 at 6009DD10.3A0F5756.jpg Type: image/jpeg Size: 13880 bytes Desc: not available URL: From liuwill14 at gmail.com Fri Nov 27 02:36:02 2015 From: liuwill14 at gmail.com (William Liu) Date: Fri, 27 Nov 2015 02:36:02 -0500 Subject: [Neuroimaging] [dipy] Installation Problem Message-ID: Hi, I have been trying to install dipy on my Windows7, tried to download the dipy folder from the link then put it into the Python34 folder, then typed 'import dipy' on python, but it was no luck. Then I decided to use the Anaconda command line: pip install dipy but there was still an error like the one in this picture ? I have also checked that I've had the other libraries like nibabel installed. What problems may I have here? Thank you in advance! Best Regards, William Liu Eletrical & Biomedical Engineering IV -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 12345.jpg Type: image/jpeg Size: 141070 bytes Desc: not available URL: From Reid.Robert at mayo.edu Fri Nov 27 13:59:46 2015 From: Reid.Robert at mayo.edu (Reid, Robert I. (Rob)) Date: Fri, 27 Nov 2015 18:59:46 +0000 Subject: [Neuroimaging] [DIPY] Comparing DIPY tensor fitting and other tools In-Reply-To: References: Message-ID: Hi, > FDT and DTIK give me identical maps (except slight difference when these two apply the mask. I see some voxels having FA>1 on FDT result). DIPY gives a map very similar FA map compared to the other two FA maps I have. Shouldn't I get an exactly same map (within rounding error maybe). You did not say how the data was weighted, so my guess is that you used the defaults, which are different. FDT (or at least dtifit, which I am more familiar with) for historical consistency defaults to no weighting when it fits the tensor to ln(S/So), which is not optimal since ln(S/So) is heteroscedastic. dtifit's -w option uses a heuristic to weight the data to account for that. IIRC, dipy determines the weights iteratively, which is theoretically better but in practice usually close to the heuristic. Rob -- Robert I. Reid, Ph.D. | Sr. Analyst/Programmer, Information Technology Aging and Dementia Imaging Research | Opus Center for Advanced Imaging Research Mayo Clinic | 200 First Street SW | Rochester, MN 55905 | mayoclinic.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From stjeansam at gmail.com Fri Nov 27 14:06:48 2015 From: stjeansam at gmail.com (Samuel St-Jean) Date: Fri, 27 Nov 2015 20:06:48 +0100 Subject: [Neuroimaging] [DIPY] Comparing DIPY tensor fitting and other tools In-Reply-To: References: Message-ID: Dipy by default uses one iteration of weighted least square, so ordinary least square, then a refit based on that. The difference probably comes from implementation details in solving the system of equations as mentioned by the previous poster, but in the end they should be mostly similar. Largest difference should be in partial volume voxel. I think there was an ismrm 2015 abstract discussing the issue of various least square fit on the fa values. On Nov 27, 2015 19:59, "Reid, Robert I. (Rob)" wrote: > Hi, > > > > > FDT and DTIK give me identical maps (except slight difference when > these two apply the mask. I see some voxels having FA>1 on FDT result). > DIPY gives a map very similar FA map compared to the other two FA maps I > have. Shouldn?t I get an exactly same map (within rounding error maybe). > > > > You did not say how the data was weighted, so my guess is that you used > the defaults, which are different. FDT (or at least dtifit, which I am > more familiar with) for historical consistency defaults to no weighting > when it fits the tensor to ln(S/So), which is not optimal since ln(S/So) is > heteroscedastic. dtifit?s -w option uses a heuristic to weight the data to > account for that. IIRC, dipy determines the weights iteratively, which is > theoretically better but in practice usually close to the heuristic. > > > > Rob > > > > -- > > Robert I. Reid, Ph.D. | Sr. Analyst/Programmer, Information Technology > > Aging and Dementia Imaging Research | Opus Center for Advanced Imaging > Research > > Mayo Clinic | 200 First Street SW | Rochester, MN 55905 | mayoclinic.org > > > > > _______________________________________________ > Neuroimaging mailing list > Neuroimaging at python.org > https://mail.python.org/mailman/listinfo/neuroimaging > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From gael.varoquaux at normalesup.org Mon Nov 30 17:45:04 2015 From: gael.varoquaux at normalesup.org (Gael Varoquaux) Date: Mon, 30 Nov 2015 23:45:04 +0100 Subject: [Neuroimaging] Mini nilearn sprint Message-ID: <20151130224504.GK308779@phare.normalesup.org> Hi all, A few of us will be sprinting on nilearn on Wednesday. We just happened to have somewhat of a free slot in our calendar (now that Alex Abraham has defended, !!!!) and want to try to get a release out. Anyhow, people are welcomed to join us, including remote. There will be a lot of activity going on. And we sure can use help for issue closing! Info here: https://github.com/nilearn/nilearn/wiki/December-2015-sprint:-Dec-2nd,-goal:-release-of-the-0.2 Cheers, Ga?l PS: Gogoteam! PPS: the 0.2 series will rock!!!