Accepted Papers

Accepted Papers

• DAPR-Net: Domain Adaptive Predicting-refinement Network for Retinal Vessel Segmentation, Zichun Huang (Shanghai Key Laboratory of Trustworthy Computing, East China Normal University); Hongyan Mao (Shanghai Key Laboratory of Trustworthy Computing, East China Normal University)*; Ningkang Jiang (Shanghai Key Laboratory of Trustworthy Computing, East China Normal University); Xiaoling Wang (Department of Electrical Engineering and Computer Science Ohio State University)

• Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-Site Neuroimaging Data, Hao Guan (University of North Carolina at Chapel Hill); Erkun Yang (University of North Carolina at Chapel Hill); Pew-Thian Yap (UNC-Chapel Hill); Dinggang Shen (The University of North Carolina at Chapel Hill); Mingxia Liu (University of North Carolina at Chapel Hill)*

• α-UNet++: A Data-driven Neural Network Architecture for Medical Image Segmentation, Yaxin Chen (Northwestern Polytechnical University); Benteng Ma (Northwestern Polytechnical University); Yong Xia (Northwestern Polytechnical University, Research & Development Institute of Northwestern Polytechnical University in Shenzhen)*

• Domain Generalizer: A Few-shot Meta Learning Framework for Domain Generalization in Medical Imaging, Pulkit Khandelwal (University of Pennsylvania)*; Paul A Yushkevich (University of Pennsylvania)

• Parts2Whole: Self-supervised Contrastive Learning via Reconstruction, Ruibin Feng (Arizona State University); Zongwei Zhou (Arizona State University); Michael Gotway (Mayo Clinic); Jianming Liang (Arizona State University, USA)*

• Cross-View Label Transfer in Knee MR Segmentation Using Iterative Context Learning, Tong Li (Shanghai Jiao Tong University)*; Kai Xuan (Shanghai Jiao Tong University); Zhong Xue (Shanghai United Imaging Intelligence Co., Ltd); Lichi Zhang (Shanghai Jiao Tong University); Dahong Qian (Shanghai Jiao Tong Univerisity); Lei Chen (Shanghai United Imaging Intelligence Co.,Ltd)

• Semi-supervised Pathology Segmentation with Disentangled Representations, Haochuan Jiang (University of Edinburgh)*; Agisilaos Chartsias (University of Edinburgh); Xinheng Zhang (University of California, Los Angeles); Giorgos Papanastasiou (University of Essex); Scott Semple (Centre for Cardiovascular Science, Edinburgh); Marc Dweck (University of Edinburgh); David Semple (University of Edinburgh); Rohan Dharmakumar (Cedars Sinai Medical Center); Sotirios Tsaftaris (The University of Edinburgh)

• Registration of Histopathogy Images Using Self Supervised Fine Grained Feature Maps, James Tong (Monash University); Dwarikanath Mahapatra (Inception Institute of Artificial Intelligence)*; Paul Bonnington (Monash University); Tom Drummond (Monash University); Zongyuan Ge (Monash)

• First U-Net Layers Contain More Domain Specific Information Than The Last Ones, Boris Shirokikh (Skoltech, IITP RAS); Ivan Zakazov (Philips Research, Skoltech)*; Alexey Chernyavskiy (Philips Research); Irina Fedulova (Philips Research); Mikhail Belyaev (Skoltech)

• Cross-Modality Segmentation by Self-Supervised Semantic Alignment in Disentangled Content Space, Junlin Yang (Yale University)*; Xiaoxiao Li (Princeton University); Daniel Pak (Yale University); Nicha Dvornek (Yale University); Julius Chapiro (Yale New Haven Hospital); MingDe Lin (Yale University); James S Duncan (Yale University)

• Continual Class Incremental Learning for CT Thoracic Segmentation, Abdelrahman Elskhawy (Technical university of Munich)*; Aneta Lisowska (Canon Medical Research Europe); Matthias Keicher (TU München); Joseph Henry (Canon Medical Research Europe Ltd.); Paul Thomson (Canon Medical Research Europe Ltd. ); Nassir Navab (Technische Universität München, Germany)

• Augmented Radiology: Patient-wise Feature Transfer Model for Glioma Grading, Zisheng Li (Hitachi Ltd.)*; Masahiro Ogino (Hitachi Ltd.)