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 ISBI 2019; bioRxiv 2020). This approach considers the probability of all possible atlas-to-image transformations and computes the ELV, thereby not relying merely on the transformation deemed optimal by the registration method. This is done without deformable registration, thus 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