Cerebral AVM segmentation from 3D rotational angiography images by convolutional neural networks

• Published in: Neuroscience informatics Vol. 3; no. 3; p. 100138
• Main Authors: Lahlouh, Mounir, Blanc, Raphaël, Piotin, Michel, Szewczyk, Jérôme, Passat, Nicolas, Chenoune, Yasmina
• Format: Journal Article
• Language: English
• Published: Elsevier Masson SAS 01.09.2023; Elsevier
• Subjects: 3D rotational angiography; Artificial Intelligence; Cerebrovascular segmentation; Computer Science; Convolutional neural networks; Focal Tversky; Fully automatic segmentation; Image Processing; Medical Imaging; Cerebrovascular segmentation; Fully automatic segmentation; 3D rotational angiography; Convolutional neural networks; Focal Tversky; convolutional neural networks; fully automatic segmentation; cerebrovascular segmentation; focal Tversky

3D rotational angiography (3DRA) provides high quality images of the cerebral arteriovenous malformation (AVM) nidus that can be reconstructed in 3D. However, these reconstructions are limited to only 3D visualization without possible interactive exploration of geometric characteristics of cerebral...