Athinoula A. Martinos Center for Biomedical Imaging Free For Non-Commercial Use Only Yes Massachusetts General Hospital / Harvard Medical School NITRC Expected Label Value (ELV) Computation for Multi-Atlas Image Soft-Segmentation OS Independent Yes MATLAB This is the public Matlab implementation for medical image soft-segmentation using the atlas-based expected label value (ELV) approach proposed by Aganj and Fischl (IEEE TMI 2021; IEEE ISBI 2019). This approach considers the probability of all possible atlas-to-image transformations and computes the ELV, without relying only on the transformation chosen as "optimal" by a registration method. This is done without deformable registration, thereby avoiding the associated computational costs. A short tutorial is included in EXAMPLE.m. 2020-10-16 Matlab codes Expected Label Value (ELV) Computation for Multi-Atlas Image Soft-Segmentation Microscopy, CT, MR, Optical Imaging, PET/SPECT, Free For Non-Commercial Use Only, OS Independent, MATLAB, Segmentation http://www.nitrc.org/projects/elv/, http://https://www.nitrc.org/projects/elv