Hi all, I have implemented the (2D) Gaussian peak detection method described in Segré et al. Nature Methods *5*, 8 (2008) <http://dx.doi.org/10.1038/nmeth.1233>. In short it is a patch based detection where a likelihood ratio (Gaussian peak vs background noise) is computed on a moving window over an image. The originality (and interest for my kind of fluorescence microscopy problems) is that this is followed by a /deflation/ step, where detected peaks are subtracted from the original image and a new detection is performed on the so called deflated image. Also it is noise resistant and there are not so many knobs to adjust (only window size, sensibility and peak radius). Is there an interest to include this in skimage? The code is available on github there <https://github.com/glyg/peak_detection>. I imagine there's room for improvements, and more compatibility with skimage standards. Cheers, Guillaume