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.
Execution Options
Download Now:
Specifications
Category:
License:
Associations
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
works well with:
Recent Activity - Documents
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