Large-scale multi-center CT and MRI segmentation of pancreas with deep learning

Zheyuan Zhang, Elif Keles, Gorkem Durak, Yavuz Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoglu, Lanhong Yao, Bin Wang, Ilkin Sevgi Isler, Linkai Peng, Hongyi Pan, Camila Lopes Vendrami, Amir Bourhani, Yury Velichko, Boqing Gong, Concetto Spampinato, Ayis Pyrros et al. (18 additional authors not shown)

Abstract: Highlights•We develop a first-ever cross-platform compatible (T1 W, T2 W, and CT) pancreas segmentation tool, named PanSegNet.•PaNSegNet has innovative “linear self-attention” blocks to reduce computational cost significantly while operating on 3D.•We shared our both source code and multi-center multi-contrast MRI datasets with ground truths.•PaNSegNet underwent rigorous validation, including cross-domain and multi-center comparisons between CT and MRI scans.