Work

LandMatch: A collaborative annotation Tool for Landmark Matching and Benchmarking 3D volumes Registration in Longitudinal Studies

Year: 2025

Type: conference-paper

Abstract: Accurate registration is an important step in longitudinal medical image studies.However, the scarcity of ground-truth annotations limits the reproducibility and benchmarking of the state-of-the-art methods.We introduce a lightweight, collaborative annotation tool for identifying the corresponding points in 3D longitudinal scans.Designed for radiologists to easily use, the tool enables a precise and scalable evaluation of registration algorithms through ground-truth landmarks.We demonstrate its application on the brain MRI longitudinal dataset BraTS-Reg and report benchmark metrics across standard registration methods.

DOI: 10.51408/csit2025_54

Authors: Gayane Kharatyan, Amel Aissaoui, Wafae Labriji, Lotfi Chaari

Institutions: Centre National de la Recherche Scientifique, Institut National Polytechnique de Toulouse, Institut de Recherche en Informatique de Toulouse, Fondation Université Française en Arménie, Université de Toulouse

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

OpenAlex ID: W4414454281

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