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22nd 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 VI. Lecture Notes in Computer Science 11769, Springer 2019, ISBN 978-3-030-32225-0
Computed Tomography
- Zhuotun Zhu, Yingda Xia, Lingxi Xie, Elliot K. Fishman, Alan L. Yuille
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Multi-scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma. 3-12 - Zihao Li, Shu Zhang, Junge Zhang, Kaiqi Huang, Yizhou Wang, Yizhou Yu:
MVP-Net: Multi-view FPN with Position-Aware Attention for Deep Universal Lesion Detection. 13-21 - Yu Zhao, Yuan Liu, Yansheng Kan, Anjany Sekuboyina, Diana Waldmannstetter, Hongwei Li
Spatial-Frequency Non-local Convolutional LSTM Network for pRCC Classification. 22-30 - Il Yong Chun, Xuehang Zheng, Yong Long, Jeffrey A. Fessler:
BCD-Net for Low-Dose CT Reconstruction: Acceleration, Convergence, and Generalization. 31-40 - Siyuan Pan, Xuhong Hou, Huating Li, Bin Sheng, Ruogu Fang
Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning. 41-49 - Mattias P. Heinrich
Closing the Gap Between Deep and Conventional Image Registration Using Probabilistic Dense Displacement Networks. 50-58 - Dan Nguyen, Azar Sadeghnejad-Barkousaraie, Chenyang Shen, Xun Jia, Steve B. Jiang:
Generating Pareto Optimal Dose Distributions for Radiation Therapy Treatment Planning. 59-67 - Naji Khosravan, Aliasghar Mortazi, Michael B. Wallace
PAN: Projective Adversarial Network for Medical Image Segmentation. 68-76 - Haofu Liao, Wei-An Lin, Zhimin Huo, Levon Vogelsang, William J. Sehnert, Shaohua Kevin Zhou, Jiebo Luo
Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction. 77-85 - Qin Liu, Xiongfeng Tang, Deming Guo, Yanguo Qin, Pengfei Jia, Yiqiang Zhan, Xiang Zhou, Dijia Wu:
Multi-class Gradient Harmonized Dice Loss with Application to Knee MR Image Segmentation. 86-94 - Jintai Chen, Yanjie Wang, Ruoqian Guo, Bohan Yu, Tingting Chen, Wenzhe Wang
LSRC: A Long-Short Range Context-Fusing Framework for Automatic 3D Vertebra Localization. 95-103 - Shikha Chaganti, Camilo Bermudez, Louise A. Mawn, Thomas A. Lasko, Bennett A. Landman:
Contextual Deep Regression Network for Volume Estimation in Orbital CT. 104-111 - Hristina Uzunova, Jan Ehrhardt, Fabian Jacob, Alex Frydrychowicz, Heinz Handels
Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images. 112-120 - Zihao Wang, Clair Vandersteen, Thomas Demarcy, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, Hervé Delingette
Deep Learning Based Metal Artifacts Reduction in Post-operative Cochlear Implant CT Imaging. 121-129 - Mohammad Arafat Hussain
ImHistNet: Learnable Image Histogram Based DNN with Application to Noninvasive Determination of Carcinoma Grades in CT Scans. 130-138 - Yuting He, Guanyu Yang, Yang Chen, Youyong Kong, Jiasong Wu, Lijun Tang, Xiaomei Zhu, Jean-Louis Dillenseger
DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy. 139-147 - Han Zheng, Lanfen Lin, Hongjie Hu, Qiaowei Zhang, Qingqing Chen, Yutaro Iwamoto, Xianhua Han, Yen-Wei Chen, Ruofeng Tong, Jian Wu:
Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior. 148-156 - Renzhen Wang, Shilei Cao, Kai Ma, Deyu Meng, Yefeng Zheng
Pairwise Semantic Segmentation via Conjugate Fully Convolutional Network. 157-165 - Boah Kim
Unsupervised Deformable Image Registration Using Cycle-Consistent CNN. 166-174 - Xudong Wang, Shizhong Han, Yunqiang Chen, Dashan Gao, Nuno Vasconcelos
Volumetric Attention for 3D Medical Image Segmentation and Detection. 175-184 - Qingyi Tao, Zongyuan Ge
Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention. 185-193 - Ke Yan, Youbao Tang, Yifan Peng
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation. 194-202 - Haofu Liao, Wei-An Lin, Jianbo Yuan, Shaohua Kevin Zhou, Jiebo Luo
Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction. 203-211 - Yulei Qin
AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networks. 212-220 - Jue Jiang, Jason Hu, Neelam Tyagi, Andreas Rimner, Sean L. Berry, Joseph O. Deasy, Harini Veeraraghavan:
Integrating Cross-modality Hallucinated MRI with CT to Aid Mediastinal Lung Tumor Segmentation. 221-229 - Tianyi Zhao, Zhaozheng Yin
Bronchus Segmentation and Classification by Neural Networks and Linear Programming. 230-239 - Takayasu Moriya, Hirohisa Oda, Midori Mitarai, Shota Nakamura, Holger R. Roth
Unsupervised Segmentation of Micro-CT Images of Lung Cancer Specimen Using Deep Generative Models. 240-248 - Mehdi Astaraki, Iuliana Toma-Dasu, Örjan Smedby, Chunliang Wang:
Normal Appearance Autoencoder for Lung Cancer Detection and Segmentation. 249-256 - Alessa Hering
mlVIRNET: Multilevel Variational Image Registration Network. 257-265 - Hao Tang, Chupeng Zhang, Xiaohui Xie:
NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation. 266-274 - Zeju Li, Han Li, Hu Han
Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition. 275-283 - Pietro Nardelli
Targeting Precision with Data Augmented Samples in Deep Learning. 284-292 - Hejie Cui
Pulmonary Vessel Segmentation Based on Orthogonal Fused U-Net++ of Chest CT Images. 293-300 - Qingbin Shao, Lijun Gong, Kai Ma, Hualuo Liu, Yefeng Zheng
Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-scale Booster. 301-309 - Valeriy Vishnevskiy, Richard Rau, Orcun Goksel
Deep Variational Networks with Exponential Weighting for Learning Computed Tomography. 310-318 - Tiancheng Shen, Xia Li, Zhisheng Zhong, Jianlong Wu, Zhouchen Lin:
R ^2 2 -Net: Recurrent and Recursive Network for Sparse-View CT Artifacts Removal. 319-327 - Rongjun Ge, Guanyu Yang, Chenchu Xu, Yang Chen, Limin Luo, Shuo Li
Stereo-Correlation and Noise-Distribution Aware ResVoxGAN for Dense Slices Reconstruction and Noise Reduction in Thick Low-Dose CT. 328-338 - Huai Chen
Harnessing 2D Networks and 3D Features for Automated Pancreas Segmentation from Volumetric CT Images. 339-347 - Chenglong Wang, Yuichiro Hayashi, Masahiro Oda
Tubular Structure Segmentation Using Spatial Fully Connected Network with Radial Distance Loss for 3D Medical Images. 348-356 - Pietro Nardelli
Bronchial Cartilage Assessment with Model-Based GAN Regressor. 357-365 - Mohamed S. Elmahdy, Jelmer M. Wolterink
Adversarial Optimization for Joint Registration and Segmentation in Prostate CT Radiotherapy. 366-374 - Anjany Sekuboyina, Markus Rempfler, Alexander Valentinitsch, Maximilian Löffler, Jan S. Kirschke, Bjoern H. Menze
Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis. 375-383 - Alexander Oliver Mader, Cristian Lorenz, Jens von Berg, Carsten Meyer:
Automatically Localizing a Large Set of Spatially Correlated Key Points: A Case Study in Spine Imaging. 384-392 - Samuel Joutard, Reuben Dorent
Permutohedral Attention Module for Efficient Non-local Neural Networks. 393-401 - Martin Zlocha, Qi Dou
Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels. 402-410
X-ray Imaging
- Yuanfeng Ji, Hao Chen
PRSNet: Part Relation and Selection Network for Bone Age Assessment. 413-421 - Yinhao Ren, Zhe Zhu, Yingzhou Li, Dehan Kong, Rui Hou, Lars J. Grimm, Jeffrey R. Marks, Joseph Y. Lo:
Mask Embedding for Realistic High-Resolution Medical Image Synthesis. 422-430 - Yuxing Tang, Youbao Tang, Veit Sandfort, Jing Xiao, Ronald M. Summers:
TUNA-Net: Task-Oriented UNsupervised Adversarial Network for Disease Recognition in Cross-domain Chest X-rays. 431-440 - Chuanbin Liu, Hongtao Xie, Sicheng Zhang, Jingyuan Xu, Jun Sun, Yongdong Zhang:
Misshapen Pelvis Landmark Detection by Spatial Local Correlation Mining for Diagnosing Developmental Dysplasia of the Hip. 441-449 - Kaiyang Cheng, Claudia Iriondo, Francesco Calivá, Justin Krogue
Adversarial Policy Gradient for Deep Learning Image Augmentation. 450-458 - Yirui Wang, Le Lu
Weakly Supervised Universal Fracture Detection in Pelvic X-Rays. 459-467 - Li Xiao, Cheng Zhu, Junjun Liu, Chunlong Luo, Peifang Liu, Yi Zhao:
Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography. 468-476 - Yuhang Liu
From Unilateral to Bilateral Learning: Detecting Mammogram Masses with Contrasted Bilateral Network. 477-485 - Heyi Li, Dongdong Chen, William H. Nailon, Mike E. Davies, David I. Laurenson:
Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis. 486-494 - Mickael Tardy
Uncertainty Measurements for the Reliable Classification of Mammograms. 495-503 - Angelica I. Avilés-Rivero, Nicolas Papadakis, Ruoteng Li, Philip Sellars, Qingnan Fan, Robby T. Tan, Carola-Bibiane Schönlieb:
GraphX $$^\mathbf{\small NET } -$$ -Chest X-Ray Classification Under Extreme Minimal Supervision. 504-512 - Jingya Liu, Liangliang Cao, Oguz Akin, Yingli Tian
3DFPN-HS ^2 2 : 3D Feature Pyramid Network Based High Sensitivity and Specificity Pulmonary Nodule Detection. 513-521 - Vaishnavi Subramanian
Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays. 522-530 - María Escobar
Hand Pose Estimation for Pediatric Bone Age Assessment. 531-539 - Zhusi Zhong
An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms. 540-548 - Sai Gokul Hariharan
Learning-Based X-Ray Image Denoising Utilizing Model-Based Image Simulations. 549-557 - Yucheng Shu, Xiao Wu, Weisheng Li:
LVC-Net: Medical Image Segmentation with Noisy Label Based on Local Visual Cues. 558-566 - Xiaoqian Jia, Sicheng Wang, Xiao Liang, Anjali Balagopal, Dan Nguyen, Ming Yang
Cone-Beam Computed Tomography (CBCT) Segmentation by Adversarial Learning Domain Adaptation. 567-575 - Haidong Zhu
Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation. 576-584 - Agostina J. Larrazabal, César Ernesto Martínez, Enzo Ferrante:
Anatomical Priors for Image Segmentation via Post-processing with Denoising Autoencoders. 585-593 - Wei Zhang, Guanbin Li, Fuyu Wang, Longjiang E, Yizhou Yu, Liang Lin, Huiying Liang:
Simultaneous Lung Field Detection and Segmentation for Pediatric Chest Radiographs. 594-602 - Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P. Harrison
Deep Esophageal Clinical Target Volume Delineation Using Encoded 3D Spatial Context of Tumors, Lymph Nodes, and Organs At Risk. 603-612 - Xi Ouyang, Zhong Xue, Yiqiang Zhan, Xiang Sean Zhou, Qingfeng Wang, Ying Zhou, Qian Wang, Jie-Zhi Cheng:
Weakly Supervised Segmentation Framework with Uncertainty: A Study on Pneumothorax Segmentation in Chest X-ray. 613-621 - Florian Kordon
Multi-task Localization and Segmentation for X-Ray Guided Planning in Knee Surgery. 622-630 - Javier Esteban, Matthias Grimm
Towards Fully Automatic X-Ray to CT Registration. 631-639 - Hendrik Burwinkel, Anees Kazi, Gerome Vivar, Shadi Albarqouni
Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph Networks. 640-648 - Maximilian Blendowski
How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning. 649-657 - Jiancheng Yang
Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis. 658-666 - Chuanbin Liu, Hongtao Xie, Yizhi Liu, Zheng-Jun Zha
Extract Bone Parts Without Human Prior: End-to-end Convolutional Neural Network for Pediatric Bone Age Assessment. 667-675 - Florin C. Ghesu, Bogdan Georgescu, Eli Gibson
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment. 676-684 - Ricardo Bigolin Lanfredi
Adversarial Regression Training for Visualizing the Progression of Chronic Obstructive Pulmonary Disease with Chest X-Rays. 685-693 - Amelia Jiménez-Sánchez
Medical-based Deep Curriculum Learning for Improved Fracture Classification. 694-702 - Hakmin Lee, Seong Tae Kim
Realistic Breast Mass Generation Through BIRADS Category. 703-711 - Shaked Perek, Lior Ness, Mika Amit, Ella Barkan, Guy Amit:
Learning from Longitudinal Mammography Studies. 712-720 - Jianbo Yuan, Haofu Liao, Rui Luo, Jiebo Luo
Automatic Radiology Report Generation Based on Multi-view Image Fusion and Medical Concept Enrichment. 721-729 - Congbo Ma, Hu Wang, Steven C. H. Hoi:
Multi-label Thoracic Disease Image Classification with Cross-Attention Networks. 730-738 - Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di-Jorio, Ghassan Hamarneh
InfoMask: Masked Variational Latent Representation to Localize Chest Disease. 739-747 - Dong Yul Oh, Jihang Kim, Kyong Joon Lee:
Longitudinal Change Detection on Chest X-rays Using Geometric Correlation Maps. 748-756 - Yunyan Xing, Zongyuan Ge
Adversarial Pulmonary Pathology Translation for Pairwise Chest X-Ray Data Augmentation. 757-765 - Prashnna Kumar Gyawali, Zhiyuan Li, Sandesh Ghimire, Linwei Wang:
Semi-supervised Learning by Disentangling and Self-ensembling over Stochastic Latent Space. 766-774 - Kailai Zhang, Nanfang Xu, Guosheng Yang, Ji Wu, Xiangling Fu
An Automated Cobb Angle Estimation Method Using Convolutional Neural Network with Area Limitation. 775-783 - Maayan Frid-Adar
Endotracheal Tube Detection and Segmentation in Chest Radiographs Using Synthetic Data. 784-792 - Ashkan Khakzar, Shadi Albarqouni
Learning Interpretable Features via Adversarially Robust Optimization. 793-800 - Gongfa Jiang, Yao Lu, Jun Wei, Yuesheng Xu:
Synthesize Mammogram from Digital Breast Tomosynthesis with Gradient Guided cGANs. 801-809 - Gerda Bortsova
Semi-supervised Medical Image Segmentation via Learning Consistency Under Transformations. 810-818 - Saeid Asgari Taghanaki
Improved Inference via Deep Input Transfer. 819-827 - Nanqing Dong, Min Xu, Xiaodan Liang, Yiliang Jiang, Wei Dai, Eric P. Xing:
Neural Architecture Search for Adversarial Medical Image Segmentation. 828-836 - Chunfeng Lian, Li Wang
MeshSNet: Deep Multi-scale Mesh Feature Learning for End-to-End Tooth Labeling on 3D Dental Surfaces. 837-845 - Feifei Xue, Jin Peng, Ruixuan Wang, Qiong Zhang, Wei-Shi Zheng:
Improving Robustness of Medical Image Diagnosis with Denoising Convolutional Neural Networks. 846-854
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