Expected Label Value (ELV) Computation for Multi-Atlas Image Soft-Segmentation
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.
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is from the makers of:
Diffusion MRI Orientation Distribution Function in Constant Solid Angle (CSA-ODF) and Hough-Transform Tractography
Image Segmentation Based on the Local Center of Mass Computation
Mid-Space-Independent and Intermediate Deformable Image Registration
Quantification of Structural Brain Connectivity via a Conductance Model
Segmentation-based Multimodal Rigid Image Registration
Tissue Thickness Estimation via Minimum Line Integrals
Wavelet-based Image Fusion
Locus Coeruleus Manual Labels for 20 HCP Subjects
Image Segmentation Based on the Local Center of Mass Computation
Mid-Space-Independent and Intermediate Deformable Image Registration
Quantification of Structural Brain Connectivity via a Conductance Model
Segmentation-based Multimodal Rigid Image Registration
Tissue Thickness Estimation via Minimum Line Integrals
Wavelet-based Image Fusion
Locus Coeruleus Manual Labels for 20 HCP Subjects
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Recent Activity - Documents
Application Publications documentation
Localization of the locus coeruleus using ELV and U-Net. posted by Iman Aganj on May 2, 2024
Article in IEEE TMI describing the methods. posted by Iman Aganj on Jun 2, 2021
ISBI paper posted by Iman Aganj on Oct 17, 2020
Recent Activity - Forums
Welcome to Open-Discussion posted by Iman Aganj on Oct 16, 2020