Accepted Papers

Multi-layer Domain Adaptation for Deep Convolutional Networks Ozan Ciga (University of Toronto)*; Jianan Chen (University of Toronto); Anne Martel (Sunnybrook Research Institute)
Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions Akihiro Fukuda (LPixel Inc.)*; Tadashi Miyamoto (LPixel Inc.); Shunsuke Kamba (The Jikei university school of medicine); Kazuki Sumiyama (The Jikei university school of medicine)
A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection Feng Zhang (Northwestern Polytechnical University); Yutong Xie (Northwestern Polytechnical University); Yong Xia (Northwestern Polytechnical University)*; Yanning Zhang (Northwestern Polytechnical University)
Temporal Consistency Objectives Regularize the Learning of Disentangled Representations Gabriele Valvano (IMT School for Advanced Studies)*; Agisilaos Chartsias (University of Edinburgh); Andrea Leo (IMT School for Advanced Studies); Sotirios Tsaftaris (The University of Edinburgh)
Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation Ilja Manakov (Ludwig Maximilian University of Munich)*; Markus Rohm (Ludwig Maximilian University of Munich); Christoph Kern (Ludwig Maximilian University of Munich); Benedikt Schworm (Ludwig Maximilian University of Munich); Karsten Kortuem (Augenklinik der Universität, Klinikum der Universität München); Volker Tresp (Siemens AG and Ludwig Maximilian University of Munich )
Intramodality Domain Adaptation using Self Ensembling and Adversarial Training Zahil Shanis (Kitware); Samuel Gerber (Kitware); Mingchen Gao (University at Buffalo); Andinet Enquobahrie (Kitware)*
Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases Barleen Kaur (McGill University)*; Paul Lemaître (McGill University); Raghav Mehta (McGill University); Nazanin Mohammadi Sepahvand (Mcgill University); Doina Precup (McGill University); Douglas Arnold (McGill University); Tal Arbel (McGill University)
Learning Interpretable Disentangled Representations using Adversarial VAEs Mhd Hasan Sarhan (Technical University of Munich)*; Abouzar Eslami (Carl Zeiss Meditec AG.); Nassir Navab (Technical University of Munich); Shadi Albarqouni (Technical University of Munich)
Synthesising Images and Labels Between MR Sequence Types With CycleGAN Eric Kerfoot (King's College London)*; Esther Puyol Anton (King's College London); Bram Ruijsink (King's College London); Rina Ariga (University of Oxford); Ernesto Zacur (University of Oxford); Pablo Lamata (King's College of London); Julia A Schnabel (King's College London)
Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images Yilin Liu (University of Wisconsin Madison); Gregory Kirk (University of Wisconsin Madison); Brendon Nacewicz (University of Wisconsin Madison); Martin A Styner (University of North Carolina Chapel Hill); Mingren Shen (University of Wisconsin Madison); Dong Nie (University of North Carolina Chapel Hill); Nagesh Adluru (University of Wisconsin Madison); Benjamin Yeske (University of Wisconsin Madison); Peter Ferrazzano (University of Wisconsin Madison); Andrew Alexander (University of Wisconsin Madison)*
Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans Yucheng Liu (Columbia University)*; Naji Khosravan (University of Central Florida); Yulin Liu (Chung Yuan Christian University); Joseph Stember (Columbia University); Jonathan Shoag (Weill Cornell Medicine); Christopher Barbieri (Weill Cornell Medicine); Ulas Bagci (University of Central Florida); Sachin Jambawalikar (Columbia University)
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning Henry Mauricio M Orbes Arteaga (King's College London)*; Thomas Varsavsky (University College London); Carole Sudre (King's College London); Zach Eaton-Rosen (University College London); Lewis Haddow (Chelsea and Westminster Hospital); Lauge Sørensen (University of Copenhagen); Mads Nielsen (University of Copenhagen); Akshay Pai (Cerebriu A/S, University of Copenhagen); Sebastien Ourselin (King's College London); Marc Modat (King's College London); Parashkev Nachev (University College London); Jorge Cardoso (Kings College London)