LesionBrain: An Online Tool for White Matter Lesion Segmentation

Pierrick Coupé (1, 2) , Thomas Tourdias (3) , Pierre Linck , Jose V Romero (4) , Jose V. Manjon (4)

1 LaBRI - Laboratoire Bordelais de Recherche en Informatique
2 PICTURA - Patch-based processing for medical and natural images
3 CHU Bordeaux
4 ITACA

In this paper, we present a new tool for white matter lesion seg-mentation called lesionBrain. Our method is based on a 3-stage strategy including multimodal patch-based segmentation, patch-based regularization of probability map and patch-based error correction using an ensemble of shallow neural networks. Its robustness and accuracy have been evaluated on the MSSEG challenge 2016 datasets. During our validation, the performance obtained by lesionBrain was competitive compared to recent deep learning methods. Moreover, lesionBrain proposes automatic lesion categorization according to location. Finally, complementary information on gray matter atrophy is included in the generated report. LesionBrain follows a software as a service model in full open access.

Mots clés: Service as a Software; Patch-based Segmentation; White Matter Lesion Segmentation

Domaines: Imagerie médicale

Pierrick Coupé, Thomas Tourdias, Pierre Linck, Jose V Romero, Jose V. Manjon. LesionBrain: An Online Tool for White Matter Lesion Segmentation. International Workshop on Patch-based Techniques in Medical Imaging (MICCAI), Sep 2018, Grenade, Spain. pp.95 - 103, ⟨10.1007/978-3-030-00500-9_11⟩. ⟨hal-01918438⟩