Abstract is missing.
- Estimating Sheets in the Heart WallTabish A. Syed, Babak Samari, Kaleem Siddiqi. 3-11 [doi]
- Automated Motion Correction and 3D Vessel Centerlines Reconstruction from Non-simultaneous Angiographic ProjectionsAbhirup Banerjee, Rajesh K. Kharbanda, Robin Choudhury, Vicente Grau. 12-20 [doi]
- Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task LearningShusil Dangi, Ziv Yaniv, Cristian A. Linte. 21-31 [doi]
- Statistical Shape Clustering of Left Atrial AppendagesJakob M. Slipsager, Kristine A. Juhl, Per E. Sigvardsen, Klaus F. Kofoed, Ole De Backer, Andy L. Olivares, Oscar Camara, Rasmus R. Paulsen. 32-39 [doi]
- Deep Learning Segmentation of the Left Ventricle in Structural CMR: Towards a Fully Automatic Multi-scan AnalysisHakim Fadil, John J. Totman, Stéphanie Marchesseau. 40-48 [doi]
- Cine and Multicontrast Late Enhanced MRI Registration for 3D Heart Model ConstructionFumin Guo, Mengyuan Li, Matthew Ng, Graham A. Wright, Mihaela Pop. 49-57 [doi]
- Joint Analysis of Personalized In-Silico Haemodynamics and Shape Descriptors of the Left Atrial AppendageJordi Mill, Andy L. Olivares, Etelvino Silva, Ibai Genua, Alvaro Fernandez, Ainhoa Aguado, Marta Nuñez Garcia, Tom de Potter, Xavier Freixa, Oscar Camara. 58-66 [doi]
- Stochastic Model-Based Left Ventricle Segmentation in 3D Echocardiography Using Fractional Brownian MotionOmar S. Al-Kadi, Allen Lu, Albert J. Sinusas, James S. Duncan. 77-84 [doi]
- Context Aware 3D Fully Convolutional Networks for Coronary Artery SegmentationYongjie Duan, Jianjiang Feng, Jiwen Lu, Jie Zhou 0001. 85-93 [doi]
- Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion AtlasEsther Puyol-Antón, Bram Ruijsink, Hélène Langet, Mathieu De Craene, Paolo Piro, Julia A. Schnabel, Andrew P. King. 94-102 [doi]
- Computational Modelling of Electro-Mechanical Coupling in the Atria and Its Changes During Atrial FibrillationSofia Monaci, David Nordsletten, Oleg V. Aslanidi. 103-113 [doi]
- High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population CohortRahman Attar, Marco Pereañez, Ali Gooya, Xènia Albà, Le Zhang, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Alejandro F. Frangi. 114-121 [doi]
- Lumen Segmentation of Aortic Dissection with Cascaded Convolutional NetworkZiyan Li, Jianjiang Feng, Zishun Feng, Yunqiang An, Yang Gao, Bin Lu, Jie Zhou 0001. 122-130 [doi]
- A Vessel-Focused 3D Convolutional Network for Automatic Segmentation and Classification of Coronary Artery Plaques in Cardiac CTAJiang Liu, Cheng Jin, Jianjiang Feng, Yubo Du, Jiwen Lu, Jie Zhou 0001. 131-141 [doi]
- Semi-automated Image Segmentation of the Midsystolic Left Ventricular Mitral Valve Complex in Ischemic Mitral RegurgitationAhmed H. Aly, Abdullah H. Aly, Mahmoud Elrakhawy, Kirlos Haroun, Luis Prieto-Riascos, Robert Gorman Jr., Natalie Yushkevich, Yoshiaki Saito, Joseph H. Gorman III, Robert C. Gorman, Paul A. Yushkevich, Alison M. Pouch. 142-151 [doi]
- Atrial Scar Segmentation via Potential Learning in the Graph-Cut FrameworkLei Li, Guang Yang 0006, Fuping Wu, Tom Wong, Raad Mohiaddin, David N. Firmin, Jenny Keegan, Lingchao Xu, Xiahai Zhuang. 152-160 [doi]
- 4D Cardiac Motion Modeling Using Pair-Wise Mesh RegistrationSiyeop Yoon, Stephen Baek, Deukhee Lee. 161-170 [doi]
- ISACHI: Integrated Segmentation and Alignment Correction for Heart ImagesBenjamin Villard, Ernesto Zacur, Vicente Grau. 171-180 [doi]
- 3D LV Probabilistic Segmentation in Cardiac MRI Using Generative Adversarial NetworkDong Yang 0005, Bo Liu 0005, Leon Axel, Dimitris N. Metaxas. 181-190 [doi]
- A Two-Stage U-Net Model for 3D Multi-class Segmentation on Full-Resolution Cardiac DataChengjia Wang, Tom MacGillivray, Gillian Macnaught, Guang Yang, David E. Newby. 191-199 [doi]
- Centreline-Based Shape Descriptors of the Left Atrial Appendage in Relation with Thrombus FormationIbai Genua, Andy L. Olivares, Etelvino Silva, Jordi Mill, Alvaro Fernandez, Ainhoa Aguado, Marta Nuñez Garcia, Tom de Potter, Xavier Freixa, Oscar Camara. 200-208 [doi]
- Automatic 3D Atrial Segmentation from GE-MRIs Using Volumetric Fully Convolutional NetworksQing Xia 0002, Yuxin Yao, Zhiqiang Hu, Aimin Hao. 211-220 [doi]
- Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour LossShuman Jia, Antoine Despinasse, Zihao Wang, Hervé Delingette, Xavier Pennec, Pierre Jaïs, Hubert Cochet, Maxime Sermesant. 221-229 [doi]
- Fully Automated Left Atrium Cavity Segmentation from 3D GE-MRI by Multi-atlas Selection and RegistrationMengyun Qiao, Yuanyuan Wang 0001, Rob J. van der Geest, Qian Tao. 230-236 [doi]
- Pyramid Network with Online Hard Example Mining for Accurate Left Atrium SegmentationCheng Bian, Xin Yang 0009, Jianqiang Ma, Shen Zheng, Yu-An Liu, Reza Nezafat, Pheng-Ann Heng, Yefeng Zheng. 237-245 [doi]
- Combating Uncertainty with Novel Losses for Automatic Left Atrium SegmentationXin Yang 0009, Na Wang, Yi Wang 0040, Xu Wang, Reza Nezafat, Dong Ni, Pheng-Ann Heng. 246-254 [doi]
- Attention Based Hierarchical Aggregation Network for 3D Left Atrial SegmentationCaizi Li, Qianqian Tong, Xiangyun Liao, Weixin Si, Yinzi Sun, Qiong Wang 0001, Pheng-Ann Heng. 255-264 [doi]
- Segmentation of the Left Atrium from 3D Gadolinium-Enhanced MR Images with Convolutional Neural NetworksChandrakanth Jayachandran Preetha, Shyamalakshmi Haridasan, Vahid Abdi, Sandy Engelhardt. 265-272 [doi]
- V-FCNN: Volumetric Fully Convolution Neural Network for Automatic Atrial SegmentationNicoló Savioli, Giovanni Montana, Pablo Lamata. 273-281 [doi]
- Ensemble of Convolutional Neural Networks for Heart SegmentationWilson Fok, Kevin Jamart, Jichao Zhao, Justin Fernandez. 282-291 [doi]
- Multi-task Learning for Left Atrial Segmentation on GE-MRIChen Chen, Wenjia Bai, Daniel Rueckert. 292-301 [doi]
- Left Atrial Segmentation Combining Multi-atlas Whole Heart Labeling and Shape-Based Atlas SelectionMarta Nuñez Garcia, Xiahai Zhuang, Gerard Sanroma, Lei Li, Lingchao Xu, Constantine Butakoff, Oscar Camara. 302-310 [doi]
- Deep Learning Based Method for Left Atrial Segmentation in GE-MRIYashu Liu 0003, Yangyang Dai, Cong Yan, Kuanquan Wang. 311-318 [doi]
- Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRISulaiman Vesal, Nishant Ravikumar, Andreas Maier 0001. 319-328 [doi]
- A Semantic-Wise Convolutional Neural Network Approach for 3-D Left Atrium Segmentation from Late Gadolinium Enhanced Magnetic Resonance ImagingDavide Borra, Alessandro Masci, Lorena Esposito, Alice Andalò, Claudio Fabbri, Cristiana Corsi. 329-338 [doi]
- Left Atrial Segmentation in a Few Seconds Using Fully Convolutional Network and Transfer LearningÉlodie Puybareau, Zhou Zhao, Younes Khoudli, Edwin Carlinet, Yongchao Xu, Jérôme Lacotte, Thierry Géraud. 339-347 [doi]
- Convolutional Neural Networks for Segmentation of the Left Atrium from Gadolinium-Enhancement MRI ImagesCoen de Vente, Mitko Veta, Orod Razeghi, Steven Niederer, Josien P. W. Pluim, Kawal S. Rhode, Rashed Karim. 348-356 [doi]
- Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium SegmentationTim Sodergren, Riddhish Bhalodia, Ross T. Whitaker, Joshua Cates, Nassir Marrouche, Shireen Y. Elhabian. 357-367 [doi]
- Left-Ventricle Quantification Using Residual U-NetEric Kerfoot, James R. Clough, Ilkay Öksüz, Jack Lee, Andrew P. King, Julia A. Schnabel. 371-380 [doi]
- Left Ventricle Full Quantification Using Deep Layer Aggregation Based Multitask Relationship LearningJiahui Li, Zhiqiang Hu. 381-388 [doi]
- Convexity and Connectivity Principles Applied for Left Ventricle Segmentation and QuantificationElias Grinias, Georgios Tziritas. 389-401 [doi]
- Calculation of Anatomical and Functional Metrics Using Deep Learning in Cardiac MRI: Comparison Between Direct and Segmentation-Based EstimationHao Xu, Jürgen E. Schneider, Vicente Grau. 402-411 [doi]
- Automated Full Quantification of Left Ventricle with Deep Neural NetworksLihong Liu, Jin Ma, Jianzong Wang, Jing Xiao. 412-420 [doi]
- ESU-P-Net: Cascading Network for Full Quantification of Left Ventricle from Cine MRIWenjun Yan, Yuanyuan Wang 0001, Shaoxiang Chen, Rob J. van der Geest, Qian Tao. 421-428 [doi]
- Left Ventricle Full Quantification via Hierarchical Quantification NetworkGuanyu Yang, Tiancong Hua, Chao Lu, Tan Pan, Xiao Yang, Liyu Hu, Jiasong Wu, Xiaomei Zhu, Huazhong Shu. 429-438 [doi]
- Automatic Left Ventricle Quantification in Cardiac MRI via Hierarchical Refinement of High-Level Features by a Salient Perceptual Grouping ModelAngélica Atehortúa, Mireille Garreau, David Romo-Bucheli, Eduardo Romero. 439-449 [doi]
- Cardiac MRI Left Ventricle Segmentation and Quantification: A Framework Combining U-Net and Continuous Max-FlowFumin Guo, Matthew Ng, Graham A. Wright. 450-458 [doi]
- Multi-estimator Full Left Ventricle Quantification Through Ensemble LearningJiasha Liu, Xiang Li 0001, Hui Ren, Quanzheng Li. 459-465 [doi]
- Left Ventricle Quantification Through Spatio-Temporal CNNsAlejandro Debus, Enzo Ferrante. 466-475 [doi]
- Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRIYeonggul Jang, Sekeun Kim, Hackjoon Shim, Hyuk-Jae Chang. 476-483 [doi]