WMH Segmentation Challenge: A Texture-Based Classification Approach

Autor(es)

Bento, Mariana ; de Souza, Roberto ; Lotufo, Roberto ; Frayne, Richard ; Rittner, Leticia ; Crimi, A ; Bakas, S ; Kuijf, H ; Menze, B ; Reyes, M

• Tipo de documento: Artigo Científico
• Fonte: BRAINLESION: GLIOMA, MULTIPLE SCLEROSIS, STROKE AND TRAUMATIC BRAIN INJURIES, BRAINLES 2017; v. 10670, p. 12-pg., 2018-01-01.

Resumo

This Grand Challenge at MICCAI 2017 aims to directly compare methods for the automatic segmentation of White Matter Hyperintensities (WMH) of presumed vascular origin. Our method automatically segment WMH by using texture-based classification of pixels within the brain white matter. It uses no a priori information about the WMH size, contrast or location. The main goal is to compute the probability of each pixel being normal or WMH tissue, by generating a probability map. Based on this probability map, we can automatically segment the WMHs. (AU)

• Processo FAPESP: 13/07559-3 - Instituto Brasileiro de Neurociência e Neurotecnologia - BRAINN
• Beneficiário: Fernando Cendes
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 12/21826-1 - Identificação Semi-Automática e Caracterização de Lesões de Substância Branca no Cérebro em Imagens Volumétricas de Ressonância Magnética
• Beneficiário: Mariana Pinheiro Bento
• Modalidade de apoio: Bolsas no Brasil - Doutorado