Program

08:30 – 09:20 Registration, speaker check-in, and poster setup

09:20 – 09:30 Opening Remarks

09:30 – 10:45 Morning Session 1: Plenary Talk

♣ Dr. Dinggang Shen: Deep Learning in Brain Quantification and Cancer Radiotherapy

10:45 – 12:30 Morning Session 2: Medical Image Segmentation

Session Chair:  Dr. Yinghuan Shi

[MLMI-O-1] Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation

Cheng Chen (The Chinese University of Hong Kong); Qi Dou (The Chinese University of Hong Kong); Hao Chen (The Chinese University of Hong Kong); Pheng-Ann Heng (The Chinese University of Hong Kong)

[MLMI-O-2] Dynamic Multi-Scale CNN Forest Learning for Automatic Cervical Cancer Segmentation

Nesrine Bnouni (LATIS Lab, ENISo-National Engineering School of Sousse, University of Sousse); Islem Rekik (University of Dundee); Mohamed Salah Rhim (LATIS Lab, ENISo – National Engineering School of Sousse, University of Sousse); Najwa Essoukri Ben Amara (University of Sousse)

[MLMI-O-3] CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

Youbao Tang (National Institutes of Health); Jinzheng Cai (University of Florida); Le Lu (NVidia Corp); Adam P Harrison (NVidia Corp); Ke Yan (NIH); Jing Xiao (Ping An Insurance (Group) Company of China); Lin Yang (University of Florida); Ronald Summers (National Institutes of Health, Bethesda, Maryland, United States)

[MLMI-O-4] Automatically Designing CNN Architectures for Medical Image Segmentation

Aliasghar Mortazi (University of Central Florida), and Ulas Bagci (University of Central Florida)

[MLMI-O-5] Iterative Interaction Training for Segmentation Editing Networks

Gustav G Bredell (ETH Zurich); Christine Tanner (ETH-Zurich); Ender Konukoglu (Department of IT and EE, ETH)

12:30 – 13:30 Lunch & Posters (can be posted until the late afternoon)

[MLMI-P-1] Classification of Pancreatic Cystic Neoplasms Based on Multimodality Images

Weixiang Chen (Tsinghua University); Ji Hongchen (Chinese PLA General Hospital); YI YU (Tsinghua University); Zhou Ruiquan (Chinese PLA General Hospital); Jie Zhou (Tsinghua University, China); Liu Rong (Chinese PLA General Hospital); Jianjiang Feng (Tsinghua University)

[MLMI-P-2] Robust Contextual Bandit via the Capped-L2 norm for Mobile Health Intervention

Feiyun Zhu (University of Texas at Arlington); Xinliang Zhu (UT Arlington); Sheng Wang (UT Arlington); Jiawen Yao (UT Arlington); Junzhou Huang (University of Texas at Arlington)

[MLMI-P-3] Multi-Task Fundus Image Quality Assessment via Transfer Learning and Landmarks Detection

Yaxin Shen (Shanghai Jiao Tong University); Bin Sheng (Shanghai Jiao Tong University); Ling Dai (Shanghai Jiao Tong University); Huating Li (Shanghai Jiao Tong University Affiliated Sixth People’s Hospital); Qiang Wu ( Shanghai Jiao Tong University Affiliated Sixth People’s Hospital); Ruogu Fang (University of Florida)

[MLMI-P-4] End-to-end Lung Nodule Detection in Computed Tomography

Dufan Wu (Massachusetts General Hospital and Harvard Medical School); Kyungsang Kim (Massachusetts General Hospital and Harvard Medical School); Bin Dong (Peking University); Georges El Fakhri (Massachusetts General Hospital and Harvard Medical School); Quanzheng Li (Massachusetts General Hospital and Harvard Medical School)

[MLMI-P-5] SCCA-ref: Novel Sparse Canonical Correlation Analysis with Reference to Discover Independent Spatial Associations between White Matter Hyperintensities and Atrophy

Gerard Sanroma (DZNE); Loes Rutten-Jacobs (DZNE); Valerie Lohner (DZNE); Johanna Kramme (DZNE); Sach Mukherjee (DZNE); Martin Reuter (German Center for Neurodegenerative Diseases); Tony Stoecker (DZNE); Monique M. B. Breteler (DZNE)

[MLMI-P-6] Ensemble of Multi-sized FCNs to Improve White Matter Lesion Segmentation

Zhewei Wang (Ohio University); Charles Smith (University of Kentucky); Jundong Liu (Ohio University)

[MLMI-P-7] Reproducible White Matter Tract Segmentation using a 3D U-Net on a Large-scale DTI Dataset

Bo Li (Erasmus Medical Center, Netherlands)

[MLMI-P-8] Deep Learning based Inter-Modality Image Registration Supervised by Intra-Modality Similarity

Xiaohuan Cao (NWPU; UNC-Chapel Hill); Jianhua Yang (NWPU); Li Wang (UNC); Zhong Xue (Shanghai United Imaging Intelligence Co., Ltd); Qian Wang (Shanghai Jiao Tong University); Dinggang Shen (UNC-Chapel Hill)

[MLMI-P-9] Brain Status Prediction with Non-negative Projective Dictionary Learning

Mingli Zhang (McGill University); Christian Desrosiers (ETS, Canada); Yuhong Guo (Carleton University); Budhachandra Khundrakpam (Mcgill University); Alan Evans (McGill University)

[MLMI-P-10] Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks

Santiago Estrada (DZNE / TUM); Sailesh Conjeti (Technical University of Munich); Muneer Ahmad Dedmari (DZNE/TUM); Martin Reuter (German Center for Neurodegenerative Diseases)

[MLMI-P-11] Joint Registration and Segmentation of Xray Images Using Generative Adversarial Networks

Dwarikanath Mahapatra (IBM Research Melbourne); Zongyuan Ge (IBM); Suman Sedai (IBM Research Australia); Rajib Chakravorty (Q-CTRL)

[MLMI-P-12] Synthesizing dynamic MRI using Long Term Recurrent Convolutional Networks

Frank Preiswerk (Brigham and Women’s Hospital, Harvard Medical School); Cheng-Chieh Cheng (Brigham and Women’s Hospital, Harvard Medical School); Jie Luo (Harvard Medical School/UTokyo); Bruno Madore (Brigham and Women’s Hospital, Harvard Medical School)

[MLMI-P-13] Computation of Total Kidney Volume from CT images in Autosomal Dominant Polycystic Kidney Disease using Multi-Task 3D Convolutional Neural Networks

Deepak Keshwani (FujiFilm Corporation); Yoshirou Kitamura (FujiFilm Corporation)

[MLMI-P-14] Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF)

Zhenghan Fang (UNC-Chapel Hill); Yong Chen (UNC-Chapel Hill); Mingxia Liu (UNC-Chapel Hill); Yiqiang Zhan (Siemens Medical Solutions, US); Weili Lin (UNC-Chapel Hill); Dinggang Shen (UNC-Chapel Hill)

[MLMI-P-15] Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features

Adrien Depeursinge (HES-SO and EPFL, Switzerland); Julien Fageot (EPFL); Vincent Andrearczyk (HES-SO Valais); John Paul Ward (North Carolina A&T State University); Michael Unser (EPFL)

[MLMI-P-16] Can Dilated Convolutions Capture Ultrasound Video Dynamics?

Mohammad Ali Maraci (University of Oxford)

[MLMI-P-17] Masseter Segmentation from Computed Tomography Using Feature-Enhanced Nested Residual Neural Network

Haifang Qin (Peking University); Yuru Pei (Peking University); Gengyu Ma (Usens Inc); Yuke Guo (Luoyang Institute of Science and Technology); Tianmin Xu (Peking University); Hongbin Zha (Peking University, China)

[MLMI-P-18] Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarchical Functional Connectivities from fMRI for Disease Diagnosis

Biao Jie (UNC-Chapel Hill); Mingxia Liu (UNC-Chapel Hill); Chunfeng Lian (UNC-Chapel Hill); Feng Shi (Shanghai United Imaging Intelligence Co., Ltd.); Dinggang Shen (UNC-Chapel Hill)

[MLMI-P-19] On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains

Enzo Ferrante (CONICET/Universidad Nacional del Litoral); Ozan Oktay (Imperial College London); Ben Glocker (Imperial College London); Diego Milone (CONICET / Universidad Nacional del Litoral)

[MLMI-P-20] Self-taught Learning with Residual Sparse Autoencoders for HEp-2 Cell Staining Pattern Recognition

Xian-Hua Han (Yamaguchi University); Yen-Wei Chen (Ritsumeikan University); Jiande Sun (Shandong Normal University)

[MLMI-P-21] Retinal Blood Vessel Segmentation using a Fully Convolutional Network-Transfer learning from Patch- to Image-level

Taibou BIRGUI SEKOU (INSA-CVL)

[MLMI-P-22] Latent3DU-net: Multi-level Latent Shape Space Constrained 3D U-net for Automatic Segmentation of the Proximal Femur from Radial MRI of the Hip

Guodong Zeng (University of Bern); Qian Wang (Shanghai Jiao Tong University); Till Lerch (Inselspital, University of Bern); Florian Schmaranzer (Inselspital, University of Bern); Moritz Tannast (Inselspital, University of Bern); Klaus Siebenrock (Inselspital, University of Bern); Guoyan Zheng (University of Bern)

[MLMI-P-23] Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes

Vanya V. Valindria, Ioannis Lavdas, Juan J. Cerrolaza, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, and Ben Glocker (Imperial College London)

[MLMI-P-24] Automatic Accurate Infant Cerebellar Tissue Segmentation with Densely Connected Convolutional Network

Jiawei Chen (University of North Carolina at Chapel Hill); Han Zhang (University of North Carolina at Chapel Hill); Dong Nie (UNC); Li Wang (UNC); Gang Li (University of North Carolina at Chapel Hill); Weili Lin (UNC-Chapel Hill); Dinggang Shen (UNC-Chapel Hill)

[MLMI-P-25] Segmentation of Clostridioides Difficile Cells in Presence of Inhomogeneous Illumination using a Deep Adversarial Network

Ali Memariani (University of Houston)

[MLMI-P-26] Combining Heterogeneously Labeled Datasets for Training Segmentation Networks

Jana Kemnitz (Paracelsus Medical University Salzburg); Ender Konukoglu (ETH Zurich); Christian Baumgartner (ETH Zuerich); Felix Eckstein (Paracelsus Medical University Salzburg); Sebastian Eder (Paracelsus Medical University Salzburg); Wolfgang Wirth (Paracelsus Medical University Salzburg)

[MLMI-P-27] Dynamic routing on Deep Neural Network for ChestX-ray Disease Classification and Sensitive Area Localization

Yan Shen (University at Buffalo); Mingchen Gao (University at Buffalo)

[MLMI-P-28] Early Automatic Classification of MR Scans of Autism Disease by Multi-Channel CNNs

Guannan Li (Biomedical Research Imaging Center, UNC-Chapel Hill); Mingxia Liu (UNC-Chapel Hill); Quansen Sun (Nanjing University of Science and Technology); Li Wang (UNC-Chapel Hill)

[MLMI-P-29] Longitudinal and Multi-modal Data Learning via Joint Embedding and Sparse Regression for Parkinson’s Disease Diagnosis

Haijun Lei (Shenzhen University); Zhongwei Huang (Shenzhen University); Ahmed Elazab (Shenzhen University); Hancong Li (Shenzhen University); Baiying Lei (Shenzhen University)

[MLMI-P-30] Prostate Cancer Classification on VERDICT DW-MRI using Convolutional Neural Networks

Eleni Chiou (University College London)

[MLMI-P-31] Detection of Pharyngeal Phases in the Videofluorographic Swallowing Study using Inflated 3D Convolutional Networks

Jong T Lee (Electronics and Telecommunications Research Institute (ETRI)); Eunhee Park (Kyungpook National University Chilgok Hospital)

[MLMI-P-32] Topological Correction of Infant Cortical Surfaces Using Anatomically Constrained U-Net

Liang Sun (UNC-Chapel Hill, Nanjing University of Aeronautics and Astronautics); Daoqiang Zhang (Nanjing University of Aeronautics and Astronautics, China); Li Wang (UNC-Chapel Hill); Wei Shao (Nanjing University of Aeronautics and Astronautics); Weili Lin (UNC-Chapel Hill); Dinggang Shen (UNC-Chapel Hill); Gang Li (UNC-Chapel Hill)

[MLMI-P-33] Regional Abnormality Representation Learning in Structural MRI for AD/MCI Diagnosis

Jun-Sik Choi (Korea University); Eunho Lee (Korea University); Heung-Il Suk (Korea University)

13:30 – 15:30 Afternoon Session 1: Computer-aided Detection/Diagnosis

Session Chair:  Dr. Mingxia Liu

[MLMI-O-6] Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs

Yuxing Tang (National Institutes of Health); Xiaosong Wang (National Institutes of Health); Adam P Harrison (NVidia Corp); Le Lu (NVidia Corp); Jing Xiao (Ping An Insurance (Group) Company of China); Ronald Summers (National Institutes of Health, Bethesda, Maryland, United States)

[MLMI-O-7] End-To-End Alzheimer’s Disease Diagnosis and Biomarker Identification

Soheil Esmaeilzadeh (Stanford University); Dimitrios Belivanis (Stanford University); Kilian Pohl (SRI); Ehsan Adeli (Stanford University)

[MLMI-O-8] Graph of Hippocampal Subfields Grading for Alzheimer’s Disease Prediction

Kilian Hett (LaBRI UMR CNRS 5800); Vinh-Thong Ta (LaBRI UMR CNRS 5800); Jose V. Manjon (ITACA Institute, Universidad Politécnica de Valencia); Pierrick Coupé (LaBRI UMR CNRS 5800)

15:30 – 16:00 Coffee Break

16:00 – 17:30 Afternoon Session 2: Automated Medical Image Analysis

Session Chair:  Dr. Li Wang (Developing Brain Computing Lab, UNC-Chapel Hill)

[MLMI-O-9] Combining Deep Learning and Active Contours Opens the Way to Robust, Automated Analysis of Brain Cytoarchitectonics

Konstantin Thierbach (Max Planck Institute for Human Cognitive and Brain Sciences); Pierre-Louis Bazin (Netherlands Institute for Neuroscience); Walter De Back (Institute for Medical Informatics and Biometry , TU Dresden); Filippos Gavriilidis (Max Planck Institute for Human Cognitive and Brain Sciences); Evgeniya Kirilina (Max Planck Institute for Human Cognitive and Brain Sciences); Carsten Jaeger (Max Planck Institute for Human Cognitive and Brain Sciences); Markus Morawski (Paul Flechsig Institute of Brain Research, University of Leipzig); Stefan Geyer (Max Planck Institute for Human Cognitive and Brain Sciences); Nikolaus Weiskopf (Max Planck Institute for Human Cognitive and Brain Sciences); Nico Scherf (Max Planck Institute for Human Cognitive and Brain Sciences)

[MLMI-O-10] Temporal Consistent 2D-3D Registration of Lateral Cephalograms and Cone-Beam Computed Tomography Images

Yungeng Zhang (Peking University); Yuru Pei (Peking University); Gengyu Ma (Usens Inc); Yuke Guo (Luoyang Institute of Science and Technology); Tianmin Xu (Peking University); Hongbin Zha (Peking University, China)

[MLMI-O-11] Deep Multiscale Convolutional Feature Learning for Weakly Supervised Localization of Chest Pathologies in X-ray Images

Suman Sedai (IBM Research Australia); Dwarikanath Mahapatra (IBM Research Australia); Zongyuan Ge (IBM Research Australia, Australia); Rajib Chakravorty (Q-CTRL); Rahil Garnavi (IBM Research Australia)

[MLMI-O-12] Adversarial Image Registration with Application for MR and TRUS Image Fusion

Pingkun Yan (Rensselaer Polytechnic Institute)

[MLMI-O-13] Nuclei Detection Using Mixture Density Network

Navid Alemi Koohbanani (University of Warwick); Ali Gooya (University of Sheffield); Mostafa Jahanifar (Tarbiat Modares University); Nasir Rajpoot (University of Warwick)

17:30 – 17:45 Closing Remarks (Best paper(s) will be announced)