<div dir="ltr"><div><span id="docs-internal-guid-edc3402e-c6d7-4ed7-ac12-442f930ec93e"><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Dear all,</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal" id="docs-internal-guid-edc3402e-c6e7-c234-3aab-787f6ef17a09"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">We are very happy to announce a new release of Diffusion Imaging in Python (Dipy).</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Here is a summary of the most important new features and developments.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">DIPY 0.8.0</span><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)"> (Released on Tuesday, 6 Jan 2015)</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Nonlinear Image-based Registration (SyN)</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">An implementation of the Symmetric Normalization method for nonlinear diffeomorphic registration. This implementation is lightweight, and does not depend on ITK or ANTS. It is written entirely in Python and Cython.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Streamline-based Linear Registration (SLR)</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">A new method that allows direct registration of bundles of streamlines. Especially useful for creating atlases of specific types of bundles.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Linear Fascicle Evaluation (LiFE)</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">This is a Python implementation of a new method for evaluation of tractrography solutions.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Sparse Fascicle Model (SFM)</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">A new signal reconstruction method , added to the large stack of reconstruction models already available in Dipy, including implementations of CSD and SHORE.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Non-local means denoising (NLMEANS)</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Denoising is a technique that can boost most of your analysis techniques as it can increase the signal to noise ratio of your data. We started this new module by implementing a very generic denoising technique that can be used also for fMRI and T1 images.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">New modular tracking machinery</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">This is a collection of new objects which allows rapid development of new fiber tracking algorithms. </span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:bold;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">In summary, since January 2014 (version 0.7.1), we closed 388 issues and merged 155 pull requests. The project now has a total of more than 4000 commits and 29 contributors.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">We would appreciate if you could forward this information to any interested individuals or labs.</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">Yours sincerely, </span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><b style="font-weight:normal"><br></b></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;color:rgb(34,34,34);font-weight:normal;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;background-color:rgb(255,255,255)">On behalf of the Dipy developers,</span></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;vertical-align:baseline;white-space:pre-wrap">Eleftherios Garyfallidis</span><br></p><p style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;vertical-align:baseline;white-space:pre-wrap"><a href="http://dipy.org">http://dipy.org</a></span></p><p style="line-height:1.15;margin-top:0pt;margin-bottom:0pt"><span style="font-size:13px;font-family:Arial;vertical-align:baseline;white-space:pre-wrap"><br></span></p></span></div></div>