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ORCID22nd MICCAI 2019: Shenzhen, China
- Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali R. Khan:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2019 - 22nd International Conference, Shenzhen, China, October 13-17, 2019, Proceedings, Part IV. Lecture Notes in Computer Science 11767, Springer 2019, ISBN 978-3-030-32250-2
Shape (Including Neuroimage Shape)
- Philipp Ernst
, Georg Hille, Christian Hansen, Klaus Tönnies, Marko Rak:
A CNN-Based Framework for Statistical Assessment of Spinal Shape and Curvature in Whole-Body MRI Images of Large Populations. 3-11 - Pan Su, Yitian Zhao, Tianhua Chen, Jianyang Xie, Yifan Zhao, Hong Qi, Yalin Zheng, Jiang Liu:
Exploiting Reliability-Guided Aggregation for the Assessment of Curvilinear Structure Tortuosity. 12-20 - Felix Ambellan, Stefan Zachow, Christoph von Tycowicz:
A Surface-Theoretic Approach for Statistical Shape Modeling. 21-29 - Xiao-Yun Zhou, Zhao-Yang Wang, Peichao Li, Jian-Qing Zheng, Guang-Zhong Yang:
One-Stage Shape Instantiation from a Single 2D Image to 3D Point Cloud. 30-38 - Sayed Mazdak Abulnaga, Esra Abaci Turk, Mikhail Bessmeltsev, Patricia Ellen Grant, Justin Solomon, Polina Golland:
Placental Flattening via Volumetric Parameterization. 39-47 - Shih-Gu Huang, Ilwoo Lyu, Anqi Qiu, Moo K. Chung:
Fast Polynomial Approximation to Heat Diffusion in Manifolds. 48-56 - Sungmin Hong, James Fishbaugh, Jason J. Wolff, Martin A. Styner, Guido Gerig:
Hierarchical Multi-geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates. 57-65 - Vianney Debavelaere, Alexandre Bône, Stanley Durrleman, Stéphanie Allassonnière:
Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories. 66-74 - Tuo Zhang, Xiao Li, Lin Zhao, Ying Huang, Zhibin He, Lei Guo, Tianming Liu:
Group-Wise Graph Matching of Cortical Gyral Hinges. 75-83 - Ying Huang, Zhibin He, Lei Guo, Tianming Liu, Tuo Zhang:
Multi-view Graph Matching of Cortical Landmarks. 84-92 - Bernhard Egger, Markus D. Schirmer, Florian Dubost, Marco J. Nardin, Natalia S. Rost, Polina Golland:
Patient-Specific Conditional Joint Models of Shape, Image Features and Clinical Indicators. 93-101 - Kristen M. Campbell, Jeffrey S. Anderson, P. Thomas Fletcher:
Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance. 102-110
Prediction
- Wei Shao, Tongxin Wang, Zhi Huang, Jun Cheng, Zhi Han, Daoqiang Zhang, Kun Huang:
Diagnosis-Guided Multi-modal Feature Selection for Prognosis Prediction of Lung Squamous Cell Carcinoma. 113-121 - Anees Kazi, Shayan Shekarforoush, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Benedikt Wiestler, Karsten Kortüm, Seyed-Ahmad Ahmadi, Shadi Albarqouni, Nassir Navab:
Graph Convolution Based Attention Model for Personalized Disease Prediction. 122-130 - Haijun Lei, Yujia Zhao, Baiying Lei:
Predicting Early Stages of Neurodegenerative Diseases via Multi-task Low-Rank Feature Learning. 131-139 - Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Heng Huang, Li Shen:
Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments over Progressions. 140-148 - Dan Hu, Han Zhang, Zhengwang Wu, Weili Lin, Gang Li, Dinggang Shen:
Deep Granular Feature-Label Distribution Learning for Neuroimaging-Based Infant Age Prediction. 149-157 - Chunfeng Lian, Mingxia Liu, Li Wang, Dinggang Shen:
End-to-End Dementia Status Prediction from Brain MRI Using Multi-task Weakly-Supervised Attention Network. 158-167 - Wonsik Jung, Ahmad Wisnu Mulyadi, Heung-Il Suk:
Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression. 168-176 - Yannan Yu, Bhargav Parsi, William Speier, Corey W. Arnold, Min Lou, Fabien Scalzo:
LSTM Network for Prediction of Hemorrhagic Transformation in Acute Stroke. 177-185 - Tao Zhou, Kim-Han Thung, Yu Zhang, Huazhu Fu, Jianbing Shen, Dinggang Shen, Ling Shao:
Inter-modality Dependence Induced Data Recovery for MCI Conversion Prediction. 186-195 - Martin Nørgaard, Brice Ozenne, Claus Svarer, Vibe G. Frokjaer, Martin Schain, Stephen C. Strother, Melanie Ganz:
Preprocessing, Prediction and Significance: Framework and Application to Brain Imaging. 196-204 - Sumana Basu, Konrad Wagstyl, Azar Zandifar, D. Louis Collins, Adriana Romero, Doina Precup:
Early Prediction of Alzheimer's Disease Progression Using Variational Autoencoders. 205-213 - Yanfu Zhang, Liang Zhan, Weidong Cai, Paul Thompson, Heng Huang:
Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions. 214-222
Detection and Localization
- Ravnoor S. Gill, Benoît Caldairou, Neda Bernasconi, Andrea Bernasconi:
Uncertainty-Informed Detection of Epileptogenic Brain Malformations Using Bayesian Neural Networks. 225-233 - Kimberlin M. H. van Wijnen, Florian Dubost, Pinar Yilmaz, Mohammad Arfan Ikram, Wiro J. Niessen, Hieab Adams, Meike W. Vernooij, Marleen de Bruijne:
Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network. 234-242 - Mingsong Zhou, Xingce Wang, Zhongke Wu, Jose M. Pozo, Alejandro F. Frangi:
Intracranial Aneurysm Detection from 3D Vascular Mesh Models with Ensemble Deep Learning. 243-252 - Jeff Craley, Emily Johnson, Christophe Jouny, Archana Venkataraman:
Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks. 253-261 - Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz:
Multiple Landmark Detection Using Multi-agent Reinforcement Learning. 262-270 - Lixi Deng, Sheng Tang, Huazhu Fu, Bin Wang, Yongdong Zhang:
Spatiotemporal Breast Mass Detection Network (MD-Net) in 4D DCE-MRI Images. 271-279 - Yi Lin, Jianchao Su, Xiang Wang, Xiang Li, Jingen Liu, Kwang-Ting Cheng, Xin Yang:
Automated Pulmonary Embolism Detection from CTPA Images Using an End-to-End Convolutional Neural Network. 280-288 - David Zimmerer, Fabian Isensee, Jens Petersen, Simon Kohl, Klaus H. Maier-Hein:
Unsupervised Anomaly Localization Using Variational Auto-Encoders. 289-297 - Sumeet Shinde, Tanay Chougule, Jitender Saini, Madhura Ingalhalikar:
HR-CAM: Precise Localization of Pathology Using Multi-level Learning in CNNs. 298-306 - Qingfeng Li, Xiaodan Xing, Ying Sun, Bin Xiao, Hao Wei, Quan Huo, Minqing Zhang, Xiang Sean Zhou, Yiqiang Zhan, Zhong Xue, Feng Shi:
Novel Iterative Attention Focusing Strategy for Joint Pathology Localization and Prediction of MCI Progression. 307-315 - Shen Zhao, Xi Wu, Bo Chen, Shuo Li:
Automatic Vertebrae Recognition from Arbitrary Spine MRI Images by a Hierarchical Self-calibration Detection Framework. 316-325
Machine Learning
- Pablo Márquez-Neila, Raphael Sznitman:
Image Data Validation for Medical Systems. 329-337 - Mohammad Alsharid, Harshita Sharma, Lior Drukker, Pierre Chatelain, Aris T. Papageorghiou, J. Alison Noble:
Captioning Ultrasound Images Automatically. 338-346 - Hariharan Ravishankar, Rahul Venkataramani, Saihareesh Anamandra, Prasad Sudhakar, Pavan Annangi:
Feature Transformers: Privacy Preserving Lifelong Learners for Medical Imaging. 347-355 - Zach Eaton-Rosen, Thomas Varsavsky, Sébastien Ourselin, M. Jorge Cardoso:
As Easy as 1, 2...4? Uncertainty in Counting Tasks for Medical Imaging. 356-364 - Chris Yoon, Ghassan Hamarneh, Rafeef Garbi:
Generalizable Feature Learning in the Presence of Data Bias and Domain Class Imbalance with Application to Skin Lesion Classification. 365-373 - Felix J. S. Bragman, Ryutaro Tanno, Sébastien Ourselin, Daniel C. Alexander, M. Jorge Cardoso:
Learning Task-Specific and Shared Representations in Medical Imaging. 374-383 - Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael B. Gotway, Jianming Liang:
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis. 384-393 - Arijit Patra, Yifan Cai, Pierre Chatelain, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble:
Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation. 394-402 - Junshen Xu, Molin Zhang, Esra Abaci Turk, Larry Zhang, Patricia Ellen Grant, Kui Ying, Polina Golland, Elfar Adalsteinsson:
Fetal Pose Estimation in Volumetric MRI Using a 3D Convolution Neural Network. 403-410 - Stefano B. Blumberg, Marco Palombo, Can Son Khoo, Chantal M. W. Tax, Ryutaro Tanno, Daniel C. Alexander:
Multi-stage Prediction Networks for Data Harmonization. 411-419 - Xinrui Zhuang, Yuexiang Li, Yifan Hu, Kai Ma, Yujiu Yang, Yefeng Zheng:
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube. 420-428 - Guilherme Pombo, Robert J. Gray, Thomas Varsavsky, John Ashburner, Parashkev Nachev:
Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning. 429-437 - Florian Dubost, Gerda Bortsova, Hieab Adams, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
Hydranet: Data Augmentation for Regression Neural Networks. 438-446 - Lei Du, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen:
A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics. 447-455 - Xiaofeng Zhu, Dinggang Shen:
Robust and Discriminative Brain Genome Association Study. 456-464 - Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Symmetric Dual Adversarial Connectomic Domain Alignment for Predicting Isomorphic Brain Graph from a Baseline Graph. 465-474 - Fenqiang Zhao, Zhengwang Wu, Li Wang, Weili Lin, Shunren Xia, Dinggang Shen, Gang Li:
Harmonization of Infant Cortical Thickness Using Surface-to-Surface Cycle-Consistent Adversarial Networks. 475-483 - Christian Wachinger, Benjamín Gutiérrez-Becker, Anna Rieckmann, Sebastian Pölsterl:
Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference. 484-492
Computer-Aided Diagnosis
- Christoph Haarburger, Michael Baumgartner, Daniel Truhn, Mirjam Broeckmann, Hannah Schneider, Simone Schrading, Christiane Kuhl, Dorit Merhof:
Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification. 495-503 - Luyang Luo, Hao Chen, Xi Wang, Qi Dou, Huangjing Lin, Juan Zhou, Gongjie Li, Pheng-Ann Heng:
Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis. 504-512 - Chaoxi Xu, Xiangjia Zhu, Wenwen He, Yi Lu, Xixi He, Zongjiang Shang, Jun Wu, Keke Zhang, Yinglei Zhang, Xianfang Rong, Zhennan Zhao, Lei Cai, Dayong Ding, Xirong Li:
Fully Deep Learning for Slit-Lamp Photo Based Nuclear Cataract Grading. 513-521 - Binh D. Nguyen, Thanh-Toan Do, Binh X. Nguyen, Tuong Do, Erman Tjiputra, Quang D. Tran:
Overcoming Data Limitation in Medical Visual Question Answering. 522-530 - Shaohua Li, Yong Liu, Xiuchao Sui, Cheng Chen, Gabriel Tjio, Daniel Shu Wei Ting, Rick Siow Mong Goh:
Multi-Instance Multi-Scale CNN for Medical Image Classification. 531-539 - Martin Holm Jensen, Dan Richter Jørgensen, Raluca Jalaboi, Mads Eiler Hansen, Martin Aastrup Olsen:
Improving Uncertainty Estimation in Convolutional Neural Networks Using Inter-rater Agreement. 540-548 - Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain, Latif Abid:
Improving Skin Condition Classification with a Visual Symptom Checker Trained Using Reinforcement Learning. 549-557 - Wenkai Yang, Juanjuan Zhao, Yan Qiang, Xiaotang Yang, Yunyun Dong, Qianqian Du, Guohua Shi, Muhammad Bilal Zia:
DScGANS: Integrate Domain Knowledge in Training Dual-Path Semi-supervised Conditional Generative Adversarial Networks and S3VM for Ultrasonography Thyroid Nodules Classification. 558-566 - Hanqiu Ju, Wanwei Jian, Xiaoping Cen, Guangyi Wang, Wu Zhou:
Similarity Steered Generative Adversarial Network and Adaptive Transfer Learning for Malignancy Characterization of Hepatocellualr Carcinoma. 567-574 - Jianan Chen, Laurent Milot, Helen M. C. Cheung, Anne L. Martel:
Unsupervised Clustering of Quantitative Imaging Phenotypes Using Autoencoder and Gaussian Mixture Model. 575-582 - Hangfan Liu, Hongming Li, Yuemeng Li, Shi Yin, Pamela Boimel, James Janopaul-Naylor, Haoyu Zhong, Ying Xiao, Edgar Ben-Josef, Yong Fan:
Adaptive Sparsity Regularization Based Collaborative Clustering for Cancer Prognosis. 583-592 - Felix Denzinger, Michael Wels, Nishant Ravikumar, Katharina Breininger, Anika Reidelshöfer, Joachim Eckert, Michael Sühling, Axel Schmermund, Andreas Maier:
Coronary Artery Plaque Characterization from CCTA Scans Using Deep Learning and Radiomics. 593-601 - Jeffrey E. Eben, Nathaniel Braman, Anant Madabhushi:
Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE). 602-610 - Jacob Antunes, Zhouping Wei, Charlems Álvarez Jimenez, Eduardo Romero, Marwa Ismail, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI. 611-619 - Zhicheng Jiao, Pu Huang, Tae-Eui Kam, Li-Ming Hsu, Ye Wu, Han Zhang, Dinggang Shen:
Dynamic Routing Capsule Networks for Mild Cognitive Impairment Diagnosis. 620-628 - Tao Zhou, Mingxia Liu, Huazhu Fu, Jun Wang, Jianbing Shen, Ling Shao, Dinggang Shen:
Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis. 629-638 - Xiaodan Xing, Qingfeng Li, Hao Wei, Minqing Zhang, Yiqiang Zhan, Xiang Sean Zhou, Zhong Xue, Feng Shi:
Dynamic Spectral Graph Convolution Networks with Assistant Task Training for Early MCI Diagnosis. 639-646 - Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman:
Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework. 647-655 - James R. Clough, Ilkay Öksüz, Esther Puyol-Antón, Bram Ruijsink, Andrew P. King, Julia A. Schnabel:
Global and Local Interpretability for Cardiac MRI Classification. 656-664 - Carole H. Sudre, Beatriz Gomez Anson, Silvia Ingala, Chris D. Lane, Daniel Jimenez, Lukas Haider, Thomas Varsavsky, Ryutaro Tanno, Lorna Smith, Sébastien Ourselin, Hans Rolf Jäger, M. Jorge Cardoso:
Let's Agree to Disagree: Learning Highly Debatable Multirater Labelling. 665-673 - Hyekyoung Lee, Moo K. Chung, Hyejin Kang, Hongyoon Choi, Seunggyun Ha, Youngmin Huh, Eunkyung Kim, Dong Soo Lee:
Coidentification of Group-Level Hole Structures in Brain Networks via Hodge Laplacian. 674-682 - Samuel Budd, Matthew Sinclair, Bishesh Khanal, Jacqueline Matthew, David Lloyd, Alberto Gómez, Nicolas Toussaint, Emma C. Robinson, Bernhard Kainz:
Confident Head Circumference Measurement from Ultrasound with Real-Time Feedback for Sonographers. 683-691
Image Reconstruction and Synthesis
- Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel:
Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space. 695-703 - Gavin Seegoolam, Jo Schlemper, Chen Qin, Anthony Price, Joseph V. Hajnal, Daniel Rueckert:
Exploiting Motion for Deep Learning Reconstruction of Extremely-Undersampled Dynamic MRI. 704-712 - Jinming Duan, Jo Schlemper, Chen Qin, Cheng Ouyang, Wenjia Bai, Carlo Biffi, Ghalib Bello, Ben Statton, Declan P. O'Regan, Daniel Rueckert:
VS-Net: Variable Splitting Network for Accelerated Parallel MRI Reconstruction. 713-722 - Luyao Shi, John A. Onofrey, Enette Mae Revilla, Takuya Toyonaga, David Menard, Joseph Ankrah, Richard E. Carson, Chi Liu, Yihuan Lu:
A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation Using Deep Learning. 723-731 - Nan Meng, Yan Yang, Zongben Xu, Jian Sun:
A Prior Learning Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging. 732-740 - Dufan Wu, Kuang Gong, Kyung Sang Kim, Xiang Li, Quanzheng Li:
Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples. 741-749 - Tian Xia, Agisilaos Chartsias, Sotirios A. Tsaftaris:
Consistent Brain Ageing Synthesis. 750-758 - Guodong Zeng, Guoyan Zheng:
Hybrid Generative Adversarial Networks for Deep MR to CT Synthesis Using Unpaired Data. 759-767 - Wei Huang, Mingyuan Luo, Xi Liu, Peng Zhang, Huijun Ding, Dong Ni:
Arterial Spin Labeling Images Synthesis via Locally-Constrained WGAN-GP Ensemble. 768-776 - Tianyang Zhang, Huazhu Fu, Yitian Zhao, Jun Cheng, Mengjie Guo, Zaiwang Gu, Bing Yang, Yuting Xiao, Shenghua Gao, Jiang Liu:
SkrGAN: Sketching-Rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis. 777-785 - Liangqiong Qu, Shuai Wang, Pew-Thian Yap, Dinggang Shen:
Wavelet-based Semi-supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI. 786-794 - Hongwei Li, Johannes C. Paetzold, Anjany Sekuboyina, Florian Kofler, Jianguo Zhang, Jan S. Kirschke, Benedikt Wiestler, Bjoern H. Menze:
DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis. 795-803
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