An ensemble of 3D convolutional neural networks for central vein detection in white matter lesions

Mário João Fartaria, Jonas Richiardi, João Jorge, Pietro Maggi, Pascal Sati, Daniel S. Reich, Reto Meuli, Cristina Granziera, Meritxell Bach Cuadra, Tobias Kober

Abstract: The presence of a vein inside white matter lesions was recently proposed as an imaging biomarker that can help in the differential diagnosis of Multiple Sclerosis (MS), potentially reducing the challenging clinical-radiological gap. Here, we propose a prototype based on ensembling small 3D convolutional networks to classify perivenular (P+) and non-perivenular (P-) lesions. Even without prior lesion masking, our approach reaches performance superior to imaging filters designed specifically to detect blood vessels, and that have access to a lesion mask.

Keywords: WM Lesions, Central Vein Sign, Automated Detection, Ensemble 3D CNN

Author Affiliation: Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare AG, Lausanne, Switzerland