TomoSAM has been developed to integrate the cutting-edge Segment Anything Model (SAM) into 3D Slicer, a highly capable software platform used for 3D image processing and visualization. SAM is a promptable deep learning model that is able to identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process. The source code associated with this article can be found at https://github.com/fsemerar/SlicerTomoSAM
@article{arxiv.2306.08609,
title = {TomoSAM: a 3D Slicer extension using SAM for tomography segmentation},
author = {Federico Semeraro and Alexandre Quintart and Sergio Fraile Izquierdo and Joseph C. Ferguson},
journal= {arXiv preprint arXiv:2306.08609},
year = {2023}
}