Thalamus Segmentation Using Deep Learning with Diffusion MRI Data: An Open Benchmark

Autor(es)

Pinheiro, Gustavo Retuci ; Brusini, Lorenza ; Carmo, Diedre ; Proa, Renata ; Abreu, Thays ; Appenzeller, Simone ; Menegaz, Gloria ; Rittner, Leticia

• Tipo de documento: Artigo Científico
• Fonte: APPLIED SCIENCES-BASEL; v. 13, n. 9, p. 21-pg., 2023-04-23.

Resumo

The thalamus is a subcortical brain structure linked to the motor system. Since certain changes within this structure are related to diseases, such as multiple sclerosis and Parkinson's, the characterization of the thalamus-e.g., shape assessment-is a crucial step in relevant studies and applications, including medical research and surgical planning. A robust and reliable thalamus-segmentation method is therefore, required to meet these demands. Despite presenting low contrast for this particular structure, T1-weighted imaging is still the most common MRI sequence for thalamus segmentation. However, diffusion MRI (dMRI) captures different micro-structural details of the biological tissue and reveals more contrast of the thalamic borders, thereby serving as a better candidate for thalamus-segmentation methods. Accordingly, we propose a baseline multimodality thalamus-segmentation pipeline that combines dMRI and T1-weighted images within a CNN approach, achieving state-of-the-art levels of Dice overlap. Furthermore, we are hosting an open benchmark with a large, preprocessed, publicly available dataset that includes co-registered, T1-weighted, dMRI, manual thalamic masks; masks generated by three distinct automated methods; and a STAPLE consensus of the masks. The dataset, code, environment, and instructions for the benchmark leaderboard can be found on our GitHub and CodaLab. (AU)

• Processo FAPESP: 19/21964-4 - Diagnóstico de doenças pulmonares e COVID a partir de imagens de tomografia computadorizada usando aprendizado profundo explicável
• Beneficiário: Diedre Santos do Carmo
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• 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