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ORCID23rd MICCAI 2020: Lima, Peru - Part IV
- Anne L. Martel
, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV. Lecture Notes in Computer Science 12264, Springer 2020, ISBN 978-3-030-59718-4
Segmentation
- Jinzheng Cai, Ke Yan, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao, Le Lu, Adam P. Harrison:
Deep Volumetric Universal Lesion Detection Using Light-Weight Pseudo 3D Convolution and Surface Point Regression. 3-13 - Julia Wolleb, Robin Sandkühler, Philippe C. Cattin:
DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision. 14-24 - Xiaohong Liu, Kai Wang, Ke Wang, Ting Chen, Kang Zhang, Guangyu Wang:
KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients. 25-34 - Haichun Yang, Ruining Deng, Yuzhe Lu, Zheyu Zhu, Ye Chen, Joseph T. Roland, Le Lu, Bennett A. Landman, Agnes B. Fogo, Yuankai Huo:
CircleNet: Anchor-Free Glomerulus Detection with Circle Representation. 35-44 - Leo K. Tam, Xiaosong Wang, Evrim Turkbey, Kevin Lu, Yuhong Wen, Daguang Xu:
Weakly Supervised One-Stage Vision and Language Disease Detection Using Large Scale Pneumonia and Pneumothorax Studies. 45-55 - Thomas Boot, Humayun Irshad:
Diagnostic Assessment of Deep Learning Algorithms for Detection and Segmentation of Lesion in Mammographic Images. 56-65 - Jhih-Yuan Lin, Yu-Cheng Chang, Winston H. Hsu:
Efficient and Phase-Aware Video Super-Resolution for Cardiac MRI. 66-76 - Xiaowei Xu, Tianchen Wang, Jian Zhuang, Haiyun Yuan, Meiping Huang, Jianzheng Cen, Qianjun Jia, Yuhao Dong, Yiyu Shi:
ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease. 77-87 - Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation. 88-97 - Shunjie Dong, Jinlong Zhao, Maojun Zhang, Zhengxue Shi, Jianing Deng, Yiyu Shi, Mei Tian, Cheng Zhuo:
DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation. 98-107 - Feng Cheng, Cheng Chen, Yukang Wang, Heshui Shi, Yukun Cao, Dandan Tu, Changzheng Zhang, Yongchao Xu:
Learning Directional Feature Maps for Cardiac MRI Segmentation. 108-117 - Lei Li, Xin Weng, Julia A. Schnabel, Xiahai Zhuang:
Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention. 118-127 - Sina Amirrajab, Samaneh Abbasi-Sureshjani, Yasmina Al Khalil, Cristian Lorenz, Jürgen Weese, Josien P. W. Pluim, Marcel Breeuwer:
XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms. 128-137 - Guohao Dong, Yaoxian Zou, Jiaming Jiao, Yuxi Liu, Shuo Liu, Tianzhu Liang, Chaoyue Liu, Zhijie Chen, Lei Zhu, Dong Ni, Muqing Lin:
TexNet: Texture Loss Based Network for Gastric Antrum Segmentation in Ultrasound. 138-145 - Rui Huang, Yuanjie Zheng, Zhiqiang Hu, Shaoting Zhang, Hongsheng Li:
Multi-organ Segmentation via Co-training Weight-Averaged Models from Few-Organ Datasets. 146-155 - Chengliang Dai, Shuo Wang, Yuanhan Mo, Kaichen Zhou, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling. 156-165 - Jiajia Chu, Yajie Chen, Wei Zhou, Heshui Shi, Yukun Cao, Dandan Tu, Ri-Chu Jin, Yongchao Xu:
Pay More Attention to Discontinuity for Medical Image Segmentation. 166-175 - Youyi Song, Zhen Yu, Teng Zhou, Jeremy Yuen-Chun Teoh, Baiying Lei, Kup-Sze Choi, Jing Qin:
Learning 3D Features with 2D CNNs via Surface Projection for CT Volume Segmentation. 176-186 - Jingkun Chen, Wenqi Li, Hongwei Li, Jianguo Zhang:
Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation. 187-196 - Zhuoying Li, Junquan Pan, Huisi Wu, Zhenkun Wen, Jing Qin:
Memory-Efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net. 197-206 - Seung Yeon Shin, Sungwon Lee, Daniel C. Elton, James L. Gulley, Ronald M. Summers:
Deep Small Bowel Segmentation with Cylindrical Topological Constraints. 207-215 - Biting Yu, Luping Zhou, Lei Wang, Wanqi Yang, Ming Yang, Pierrick Bourgeat, Jurgen Fripp:
Learning Sample-Adaptive Intensity Lookup Table for Brain Tumor Segmentation. 216-226 - Hang Li, Dong Wei, Shilei Cao, Kai Ma, Liansheng Wang, Yefeng Zheng:
Superpixel-Guided Label Softening for Medical Image Segmentation. 227-237 - Xing Tao, Yuexiang Li, Wenhui Zhou, Kai Ma, Yefeng Zheng:
Revisiting Rubik's Cube: Self-supervised Learning with Volume-Wise Transformation for 3D Medical Image Segmentation. 238-248 - Tianwei Zhang, Lequan Yu, Na Hu, Su Lv, Shi Gu:
Robust Medical Image Segmentation from Non-expert Annotations with Tri-network. 249-258 - Benoît Audelan, Dimitri Hamzaoui, Sarah Montagne, Raphaële Renard-Penna, Hervé Delingette:
Robust Fusion of Probability Maps. 259-268 - Marcus Nordström, Han Bao, Fredrik Löfman, Henrik Hult, Atsuto Maki, Masashi Sugiyama:
Calibrated Surrogate Maximization of Dice. 269-278 - Guotai Wang, Michael Aertsen, Jan Deprest, Sébastien Ourselin, Tom Vercauteren, Shaoting Zhang:
Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices. 279-288 - Frederic Madesta, Rüdiger Schmitz, Thomas Rösch, René Werner:
Widening the Focus: Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies. 289-298 - Udaranga Wickramasinghe, Edoardo Remelli, Graham Knott, Pascal Fua:
Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data. 299-308 - Youyi Song, Teng Zhou, Jeremy Yuen-Chun Teoh, Jing Zhang, Jing Qin:
Unsupervised Learning for CT Image Segmentation via Adversarial Redrawing. 309-320 - Mo Zhang, Bin Dong, Quanzheng Li:
Deep Active Contour Network for Medical Image Segmentation. 321-331 - Luyan Liu, Kai Ma, Yefeng Zheng:
Learning Crisp Edge Detector Using Logical Refinement Network. 332-341 - Qi Liu, Han Jiang, Tao Liu, Zihao Liu, Sicheng Li, Wujie Wen, Yiyu Shi:
Defending Deep Learning-Based Biomedical Image Segmentation from Adversarial Attacks: A Low-Cost Frequency Refinement Approach. 342-351 - Yanda Meng, Meng Wei, Dongxu Gao, Yitian Zhao, Xiaoyun Yang, Xiaowei Huang, Yalin Zheng:
CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation. 352-362 - Jeya Maria Jose Valanarasu, Vishwanath A. Sindagi, Ilker Hacihaliloglu, Vishal M. Patel:
KiU-Net: Towards Accurate Segmentation of Biomedical Images Using Over-Complete Representations. 363-373 - Wentao Zhu, Can Zhao, Wenqi Li, Holger Roth, Ziyue Xu, Daguang Xu:
LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation. 374-384 - Grzegorz Jacenków, Alison Q. O'Neil, Brian Mohr, Sotirios A. Tsaftaris:
INSIDE: Steering Spatial Attention with Non-imaging Information in CNNs. 385-395 - Haomiao Ni, Yuan Xue, Qian Zhang, Xiaolei Huang:
SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos. 396-405 - Zihao Liu, Sicheng Li, Yen-Kuang Chen, Tao Liu, Qi Liu, Xiaowei Xu, Yiyu Shi, Wujie Wen:
Orchestrating Medical Image Compression and Remote Segmentation Networks. 406-416 - Han Li, Hu Han, S. Kevin Zhou:
Bounding Maps for Universal Lesion Detection. 417-428 - Shaocong Mo, Ming Cai, Lanfen Lin, Ruofeng Tong, Qingqing Chen, Fang Wang, Hongjie Hu, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen:
Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks. 429-438 - Yanan Ruan, Dengwang Li, Harry Marshall, Timothy Miao, Tyler Cossetto, Ian Chan, Omar Daher, Fabio Accorsi, Aashish Goela, Shuo Li:
Mt-UcGAN: Multi-task Uncertainty-Constrained GAN for Joint Segmentation, Quantification and Uncertainty Estimation of Renal Tumors on CT. 439-449 - Hao Zheng, Zhiguo Zhuang, Yulei Qin, Yun Gu, Jie Yang, Guang-Zhong Yang:
Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations. 450-459 - Xixi Jiang, Qingqing Luo, Zhiwei Wang, Tao Mei, Yu Wen, Xin Li, Kwang-Ting Cheng, Xin Yang:
Multi-phase and Multi-level Selective Feature Fusion for Automated Pancreas Segmentation from CT Images. 460-469 - Xuanang Xu, Chunfeng Lian, Shuai Wang, Andrew Z. Wang, Trevor J. Royce, Ronald C. Chen, Jun Lian, Dinggang Shen:
Asymmetrical Multi-task Attention U-Net for the Segmentation of Prostate Bed in CT Image. 470-479 - Haozhe Jia, Yong Xia, Weidong Cai, Heng Huang:
Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images. 480-490 - Ling Zhang, Yu Shi, Jiawen Yao, Yun Bian, Kai Cao, Dakai Jin, Jing Xiao, Le Lu:
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-institutional Multi-phase Partially-Annotated CT Scans. 491-500 - Hristina Uzunova, Jan Ehrhardt, Heinz Handels:
Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks. 501-511 - Youbao Tang, Yuxing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers:
E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans. 512-522 - Boris Shirokikh, Alexey Shevtsov, Anvar Kurmukov, Alexandra Dalechina, Egor Krivov, Valery Kostjuchenko, Andrey Golanov, Mikhail Belyaev:
Universal Loss Reweighting to Balance Lesion Size Inequality in 3D Medical Image Segmentation. 523-532 - Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation. 533-541 - Shu Zhang, Jincheng Xu, Yu-Chun Chen, Jiechao Ma, Zihao Li, Yizhou Wang, Yizhou Yu:
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices. 542-551 - Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI. 552-561 - Jiancheng Yang, Yi He, Xiaoyang Huang, Jingwei Xu, Xiaodan Ye, Guangyu Tao, Bingbing Ni:
AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes. 562-572 - Youbao Tang, Ke Yan, Jing Xiao, Ronald M. Summers:
One Click Lesion RECIST Measurement and Segmentation on CT Scans. 573-583 - Francesco La Rosa, Erin S. Beck, Ahmed Abdulkadir, Jean-Philippe Thiran, Daniel S. Reich, Pascal Sati, Meritxell Bach Cuadra:
Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI. 584-593 - Xin Yu, Bin Lou, Donghao Zhang, David J. Winkel, Nacim Arrahmane, Mamadou Diallo, Tongbai Meng, Heinrich von Busch, Robert Grimm, Berthold Kiefer, Dorin Comaniciu, Ali Kamen:
Deep Attentive Panoptic Model for Prostate Cancer Detection Using Biparametric MRI Scans. 594-604
Shape Models and Landmark Detection
- Tao Liu, Yun Tian, Shifeng Zhao, Xiaoying Huang:
Graph Reasoning and Shape Constraints for Cardiac Segmentation in Congenital Heart Defect. 607-616 - Martin Hanik, Hans-Christian Hege, Anja Hennemuth, Christoph von Tycowicz:
Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines. 617-626 - Riddhish Bhalodia, Ladislav Kavan, Ross T. Whitaker:
Self-supervised Discovery of Anatomical Shape Landmarks. 627-638 - Youyi Song, Lei Zhu, Baiying Lei, Bin Sheng, Qi Dou, Jing Qin, Kup-Sze Choi:
Shape Mask Generator: Learning to Refine Shape Priors for Segmenting Overlapping Cervical Cytoplasms. 639-649 - Shaheer U. Saeed, Zeike A. Taylor, Mark A. Pinnock, Mark Emberton, Dean C. Barratt, Yipeng Hu:
Prostate Motion Modelling Using Biomechanically-Trained Deep Neural Networks on Unstructured Nodes. 650-659 - Yanhao Zhang, Raphael Falque, Liang Zhao, Shoudong Huang, Boni Hu:
Deep Learning Assisted Automatic Intra-operative 3D Aortic Deformation Reconstruction. 660-669 - Wei Liu, Yu Wang, Tao Jiang, Ying Chi, Lei Zhang, Xian-Sheng Hua:
Landmarks Detection with Anatomical Constraints for Total Hip Arthroplasty Preoperative Measurements. 670-679 - Zhao-Yang Wang, Xiao-Yun Zhou, Peichao Li, Celia Theodoreli-Riga, Guang-Zhong Yang:
Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle. 680-691 - Qingsong Yao, Zecheng He, Hu Han, S. Kevin Zhou:
Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection. 692-702 - Diya Sun, Yuru Pei, Peixin Li, Guangying Song, Yuke Guo, Hongbin Zha, Tianmin Xu:
Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model. 703-712 - Katharina Breininger, Marcus Pfister, Markus Kowarschik, Andreas K. Maier:
Move Over There: One-Click Deformation Correction for Image Fusion During Endovascular Aortic Repair. 713-723 - Micha Pfeiffer, Carina Riediger, Stefan Leger, Jens-Peter Kühn, Danilo Seppelt, Ralf-Thorsten Hoffmann, Jürgen Weitz, Stefanie Speidel:
Non-Rigid Volume to Surface Registration Using a Data-Driven Biomechanical Model. 724-734 - Nazim Haouchine, Parikshit Juvekar, William M. Wells III, Stephane Cotin, Alexandra J. Golby, Sarah F. Frisken:
Deformation Aware Augmented Reality for Craniotomy Using 3D/2D Non-rigid Registration of Cortical Vessels. 735-744 - Jaesin Ahn, Hyun-Joo Lee, Inchul Choi, Minho Lee:
Skip-StyleGAN: Skip-Connected Generative Adversarial Networks for Generating 3D Rendered Image of Hand Bone Complex. 745-754 - Jean-Rassaire Fouefack, Bhushan Borotikar, Tania S. Douglas, Valérie Burdin, Tinashe E. M. Mutsvangwa:
Dynamic Multi-object Gaussian Process Models. 755-764 - Matthias Wilms, Jan Ehrhardt, Nils D. Forkert:
A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data. 765-775 - Bente Thamsen, Pavlo Yevtushenko, Lina Gundelwein, Hans Lamecker, Titus Kühne, Leonid Goubergrits:
Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta. 776-785 - Yonghui Fan, Yalin Wang:
Convolutional Bayesian Models for Anatomical Landmarking on Multi-dimensional Shapes. 786-796 - Jesse Sun, Fatemeh Darbeha, Mark Zaidi, Bo Wang:
SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation. 797-806 - Chunfeng Lian, Fan Wang, Hannah H. Deng, Li Wang, Deqiang Xiao, Tianshu Kuang, Hung-Ying Lin, Jaime Gateno, Steve Guo-Fang Shen, Pew-Thian Yap, James J. Xia, Dinggang Shen:
Multi-task Dynamic Transformer Network for Concurrent Bone Segmentation and Large-Scale Landmark Localization with Dental CBCT. 807-816 - Yankun Lang, Chunfeng Lian, Deqiang Xiao, Hannah H. Deng, Peng Yuan, Jaime Gateno, Steve Guo-Fang Shen, David M. Alfi, Pew-Thian Yap, James J. Xia, Dinggang Shen:
Automatic Localization of Landmarks in Craniomaxillofacial CBCT Images Using a Local Attention-Based Graph Convolution Network. 817-826
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