Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data: First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings

Front Matter ....Pages i-xvii
Front Matter ....Pages 1-1
 Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation  (Ilja Manakov, Markus Rohm, Christoph Kern, Benedikt Schworm, Karsten Kortuem, Volker Tresp)....Pages 3-10
 Temporal Consistency Objectives Regularize the Learning of Disentangled Representations  (Gabriele Valvano, Agisilaos Chartsias, Andrea Leo, Sotirios A. Tsaftaris)....Pages 11-19
 Multi-layer Domain Adaptation for Deep Convolutional Networks  (Ozan Ciga, Jianan Chen, Anne Martel)....Pages 20-27
 Intramodality Domain Adaptation Using Self Ensembling and Adversarial Training  (Zahil Shanis, Samuel Gerber, Mingchen Gao, Andinet Enquobahrie)....Pages 28-36
 Learning Interpretable Disentangled Representations Using Adversarial VAEs  (Mhd Hasan Sarhan, Abouzar Eslami, Nassir Navab, Shadi Albarqouni)....Pages 37-44
 Synthesising Images and Labels Between MR Sequence Types with CycleGAN  (Eric Kerfoot, Esther Puyol-Antón, Bram Ruijsink, Rina Ariga, Ernesto Zacur, Pablo Lamata et al.)....Pages 45-53
 Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning  (Mauricio Orbes-Arteaga, Thomas Varsavsky, Carole H. Sudre, Zach Eaton-Rosen, Lewis J. Haddow, Lauge Sørensen et al.)....Pages 54-62
 Cross-Modality Knowledge Transfer for Prostate Segmentation from CT Scans  (Yucheng Liu, Naji Khosravan, Yulin Liu, Joseph Stember, Jonathan Shoag, Ulas Bagci et al.)....Pages 63-71
 A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection  (Feng Zhang, Yutong Xie, Yong Xia, Yanning Zhang)....Pages 72-80
 Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images  (Yilin Liu, Gregory R. Kirk, Brendon M. Nacewicz, Martin A. Styner, Mingren Shen, Dong Nie et al.)....Pages 81-89
 Improving Pathological Structure Segmentation via Transfer Learning Across Diseases  (Barleen Kaur, Paul Lemaître, Raghav Mehta, Nazanin Mohammadi Sepahvand, Doina Precup, Douglas Arnold et al.)....Pages 90-98
 Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions  (Akihiro Fukuda, Tadashi Miyamoto, Shunsuke Kamba, Kazuki Sumiyama)....Pages 99-107
Front Matter ....Pages 109-109
 Self-supervised Learning of Inverse Problem Solvers in Medical Imaging  (Ortal Senouf, Sanketh Vedula, Tomer Weiss, Alex Bronstein, Oleg Michailovich, Michael Zibulevsky)....Pages 111-119
 Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-Propagation  (Shiqi Peng, Bolin Lai, Guangyu Yao, Xiaoyun Zhang, Ya Zhang, Yan-Feng Wang et al.)....Pages 120-128
 A Cascade Attention Network for Liver Lesion Classification in Weakly-Labeled Multi-phase CT Images  (Xiao Chen, Lanfen Lin, Hongjie Hu, Qiaowei Zhang, Yutaro Iwamoto, Xianhua Han et al.)....Pages 129-138
 CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT  (Bo Zhou, Adam P. Harrison, Jiawen Yao, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao et al.)....Pages 139-147
 Active Learning Technique for Multimodal Brain Tumor Segmentation Using Limited Labeled Images  (Dhruv Sharma, Zahil Shanis, Chandan K. Reddy, Samuel Gerber, Andinet Enquobahrie)....Pages 148-156
 Semi-supervised Learning of Fetal Anatomy from Ultrasound  (Jeremy Tan, Anselm Au, Qingjie Meng, Bernhard Kainz)....Pages 157-164
 Multi-modal Segmentation with Missing MR Sequences Using Pre-trained Fusion Networks  (Karin van Garderen, Marion Smits, Stefan Klein)....Pages 165-172
 More Unlabelled Data or Label More Data? A Study on Semi-supervised Laparoscopic Image Segmentation  (Yunguan Fu, Maria R. Robu, Bongjin Koo, Crispin Schneider, Stijn van Laarhoven, Danail Stoyanov et al.)....Pages 173-180
 Few-Shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition  (Santi Puch, Irina Sánchez, Matt Rowe)....Pages 181-189
 A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Image Segmentation  (Erica M. Rutter, John H. Lagergren, Kevin B. Flores)....Pages 190-198
 Transfer Learning from Partial Annotations for Whole Brain Segmentation  (Chengliang Dai, Yuanhan Mo, Elsa Angelini, Yike Guo, Wenjia Bai)....Pages 199-206
 Learning to Segment Skin Lesions from Noisy Annotations  (Zahra Mirikharaji, Yiqi Yan, Ghassan Hamarneh)....Pages 207-215
 A Weakly Supervised Method for Instance Segmentation of Biological Cells  (Fidel A. Guerrero-Peña, Pedro D. Marrero Fernandez, Tsang Ing Ren, Alexandre Cunha)....Pages 216-224
 Towards Practical Unsupervised Anomaly Detection on Retinal Images  (Khalil Ouardini, Huijuan Yang, Balagopal Unnikrishnan, Manon Romain, Camille Garcin, Houssam Zenati et al.)....Pages 225-234
 Fine Tuning U-Net for Ultrasound Image Segmentation: Which Layers?  (Mina Amiri, Rupert Brooks, Hassan Rivaz)....Pages 235-242
 Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance  (Toan Duc Bui, Li Wang, Jian Chen, Weili Lin, Gang Li, Dinggang Shen)....Pages 243-251
Back Matter ....Pages 253-254