An attention residual u-net with differential preprocessing and geometric postprocessing: Learning how to segment vasculature including intracranial aneurysms

Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Jinshan Tang, Jingfeng Jiang

Abstract: Highlights•This paper proposes automatically segmenting vasculature, including intracranial aneurysms, from 3DRA images with the need for “patient-specific” computational hemodynamics.•An attention residual U-Net with preprocessing and postprocessing is constructed.•We design multi-scale supervision to improve the segmentation of small vessels.•We adopt a fully connected 3D conditional random field to remove unwanted vessel-to-vessel or vessel-to-aneurysm connections.•This is the first study to systematically investigate the potential of deep-learning image segmentation for “patient-specific” computational hemodynamics.