Article

Exploiting XAI maps to improve MS lesion segmentation and detection in MRI

2024-08-30

Abstract excerpt

To date, several methods have been developed to explain deep learning algorithms for classification tasks. Recently, an adaptation of two of such methods has been proposed to generate instance-level explainable maps in a semantic segmentation scenario, such as multiple sclerosis (MS) lesion segmentation. In the mentioned work, a 3D U-Net was trained and tested for MS lesion segmentation, yielding an F1 score of 0....

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: fa32f8bb-5670-5539-8a9a-b5f390227799
DOI: 10.1101/2024.08.29.610090

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Exploiting XAI maps to improve MS lesion segmentation and detection in MRIDOI 10.1101/2024.08.29.610090Read

Precision Lesion Profiling in Multiple Sclerosis: A Novel Pipeline for EDSS PredictionSemantic proximity Read

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRISemantic proximity Read

SibBMS: Siberian Brain Multiple Sclerosis Dataset with lesion segmentation and patient meta informationSemantic proximity Read

A Siamese U-Transformer for change detection on MRI brain for multiple sclerosis, a model development and external validation studySemantic proximity Read

An Explainable SSL-Based Model for Robust Multi-Class Brain Tumor Classification from MRI ImagesSemantic proximity Read

A geometric-to-neural cascade for cerebral microbleed detection in susceptibility-weighted MRISemantic proximity Read

Automated Detection of Lacunes in Brain MR Images Using SAM with Robust Prompts via Self-Distillation and Anatomy-Informed PriorsSemantic proximity Read

Automatic Segmentation of White Matter Hyperintensities from Brain Magnetic Resonance Images in the Era of Deep Learning and Big Data – A Systematic ReviewSemantic proximity Read

AI-Generated Data Improves Multiple Sclerosis Classification in a Basal Ganglia Radiomics ModelSemantic proximity Read

Multi-parametric MRI phenotype with trustworthy machine learning for differentiating CNS demyelinating diseases.Semantic proximity Read

Explainable 3D CNNs link regional and network level disruption in early Parkinson’s MRIs to symptom progressionSemantic proximity Read

Deep learning-based detection and segmentation of diffusion abnormalities in acute ischemic strokeSemantic proximity Read