Dear all, I would like to point out to our new paper: *Deep learning enabled multi-organ segmentation of mouse embryos *by Rolfe et al. It is publicly available at https://journals.biologists.com/bio/article/12/2/bio059698/287076/Deep-learning-enabled-multi-organ-segmentation-of
Paper describes and evaluates the outcomes of a deep-learning segmentation network we trained using diceCT scans of E15 wild-type mice from IMPC, and the published anatomical atlas. The companion tool, *MEMOS, *is now available as a part of the 3D Slicer extension catalog. MEMOS is independent of the existing SlicerMorph extension, and you need to install separately. When a high-end GPU (16GB minimum GPU RAM required) is available, segmentation of 50 organs takes about 40-60 secs. If a GPU is not available, it defaults to CPU based inference, which is substantially longer at 10-40 minutes, depending on the number of cpu cores available. Installation instructions, along with a sample E15 fetal scan from IMPC is available at the official repository https://github.com/SlicerMorph/MEMOS. Here is a brief video of how the tool is used. https://twitter.com/i/status/1628172435030937600 -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to morphmet2+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/morphmet2/a5cd2e59-af39-4732-af31-941151da801an%40googlegroups.com.