AUTHORS: Wynen M., Macias Gordaliza P., Stölting A., Maggi P., Bach Cuadra M., Macq B.

International Society for Magnetic Resonance in Medicine, : , Singapore, May 2024

ABSTRACT

Motivation

Accurate white matter lesion (WML) counting and delineation are crucial for multiple sclerosis (MS) diagnosis and prognosis. Though being a critical step in clinical research and automated tools relying on lesion-centered patches, no previous work studied post-processing methods to transform voxel-wise segmentations into lesion instance masks in MS.

Goal(s):

In this study, we compare the conventional connected components (CC) method to a confluent lesion splitting (CLS) method that was used but never validated.

Approach:

CC and CLS’s performances are evaluated using three common lesion segmentation tools (LSTs): SPM, SAMSEG, and nnU-Net.

Results:

CLS lacks generalization, sacrifices specificity for sensitivity and worsens segmentation quality.

Impact:

Our results underscore the need for the development of a novel instance segmentation methodology that accounts for (i) the potential large distance between voxels and the center of the lesions to which they belong and (ii) confluent lesions.

BibTex

Module: