Abstract is missing.
- A Persistent Homology-Based Topological Loss Function for Multi-class CNN Segmentation of Cardiac MRINick Byrne, James R. Clough, Giovanni Montana, Andrew P. King. 3-13 [doi]
- Automatic Multiplanar CT Reformatting from Trans-Axial into Left Ventricle Short-Axis ViewMarta Nuñez Garcia, Nicolas Cedilnik, Shuman Jia, Maxime Sermesant, Hubert Cochet. 14-22 [doi]
- Graph Convolutional Regression of Cardiac Depolarization from Sparse Endocardial MapsFelix Meister, Tiziano Passerini, Chloé Audigier, Èric Lluch, Viorel Mihalef, Hiroshi Ashikaga, Andreas Maier 0001, Henry R. Halperin, Tommaso Mansi. 23-34 [doi]
- A Cartesian Grid Representation of Left Atrial Appendages for a Deep Learning Estimation of Thrombogenic Risk PredictorsCésar Acebes, Xabier Morales, Oscar Camara. 35-43 [doi]
- Measure Anatomical Thickness from Cardiac MRI with Deep Neural NetworksQiaoying Huang, Eric Z. Chen, Hanchao Yu, Yimo Guo, Terrence Chen, Dimitris N. Metaxas, Shanhui Sun. 44-55 [doi]
- Modelling Cardiac Motion via Spatio-Temporal Graph Convolutional Networks to Boost the Diagnosis of Heart ConditionsPing Lu, Wenjia Bai, Daniel Rueckert, J. Alison Noble. 56-65 [doi]
- Towards Mesh-Free Patient-Specific Mitral Valve ModelingJudit Ros, Oscar Camara, Uxio Hermida, Bart H. Bijnens, Hernán G. Morales. 66-75 [doi]
- PIEMAP: Personalized Inverse Eikonal Model from Cardiac Electro-Anatomical MapsThomas Grandits, Simone Pezzuto, Jolijn M. Lubrecht, Thomas Pock, Gernot Plank, Rolf Krause. 76-86 [doi]
- Automatic Detection of Landmarks for Fast Cardiac MR Image RegistrationMia Mojica, Mihaela Pop, Mehran Ebrahimi. 87-96 [doi]
- Quality-Aware Semi-supervised Learning for CMR SegmentationBram Ruijsink, Esther Puyol-Antón, Ye Li, Wenjia Bai, Eric Kerfoot, Reza Razavi, Andrew P. King. 97-107 [doi]
- Estimation of Imaging Biomarker's Progression in Post-infarct Patients Using Cross-sectional DataMarta Nuñez Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, Maxime Sermesant. 108-116 [doi]
- PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT DataMeng Ye, Qiaoying Huang, Dong Yang 0005, Pengxiang Wu, Jingru Yi, Leon Axel, Dimitris N. Metaxas. 117-126 [doi]
- Left Atrial Ejection Fraction Estimation Using SEGANet for Fully Automated Segmentation of CINE MRIAna Lourenço, Eric Kerfoot, Connor Dibblin, Ebraham Alskaf, Mustafa Anjari, Anil A. Bharath, Andrew P. King, Henry Chubb, Teresa Correia, Marta Varela. 137-145 [doi]
- Estimation of Cardiac Valve Annuli Motion with Deep LearningEric Kerfoot, Carlos Escudero King, Tefvik Ismail, David Nordsletten, Renee Miller. 146-155 [doi]
- 4D Flow Magnetic Resonance Imaging for Left Atrial Haemodynamic Characterization and Model CalibrationXabier Morales, Jordi Mill, Gaspar Delso, Filip Loncaric, Ada Doltra, Xavier Freixa, Marta Sitges, Bart H. Bijnens, Oscar Camara. 156-165 [doi]
- Segmentation-Free Estimation of Aortic Diameters from MRI Using Deep LearningAxel Aguerreberry, Ezequiel de la Rosa, Alain Lalande, Elmer Fernandez. 166-174 [doi]
- Histogram Matching Augmentation for Domain Adaptation with Application to Multi-centre, Multi-vendor and Multi-disease Cardiac Image SegmentationJun Ma. 177-186 [doi]
- Disentangled Representations for Domain-Generalized Cardiac SegmentationXiao Liu, Spyridon Thermos, Agisilaos Chartsias, Alison O'Neil, Sotirios A. Tsaftaris. 187-195 [doi]
- A 2-Step Deep Learning Method with Domain Adaptation for Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Magnetic Resonance SegmentationJorge Corral Acero, Vaanathi Sundaresan, Nicola K. Dinsdale, Vicente Grau, Mark Jenkinson. 196-207 [doi]
- Random Style Transfer Based Domain Generalization Networks Integrating Shape and Spatial InformationLei Li 0020, Veronika A. Zimmer, Wangbin Ding, Fuping Wu, Liqin Huang, Julia A. Schnabel, Xiahai Zhuang. 208-218 [doi]
- Semi-supervised Cardiac Image Segmentation via Label Propagation and Style TransferYao Zhang, Jiawei Yang, Feng Hou, Yang Liu, Yixin Wang, Jiang Tian, Cheng Zhong, Yang Zhang, Zhiqiang He. 219-227 [doi]
- Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image SegmentationCian M. Scannell, Amedeo Chiribiri, Mitko Veta. 228-237 [doi]
- Studying Robustness of Semantic Segmentation Under Domain Shift in Cardiac MRIPeter M. Full, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein. 238-249 [doi]
- A Deep Convolutional Neural Network Approach for the Segmentation of Cardiac Structures from MRI SequencesAdam Carscadden, Michelle Noga, Kumaradevan Punithakumar. 250-258 [doi]
- Multi-center, Multi-vendor, and Multi-disease Cardiac Image Segmentation Using Scale-Independent Multi-gate UNETMina Saber, Dina Abdelrauof, Mustafa Elattar. 259-268 [doi]
- Adaptive Preprocessing for Generalization in Cardiac MR Image SegmentationFiras Khader, Justus Schock, Daniel Truhn, Fabian Morsbach, Christoph Haarburger. 269-276 [doi]
- Deidentifying MRI Data Domain by Iterative BackpropagationMario Parreño, Roberto Paredes, Alberto Albiol. 277-286 [doi]
- A Generalizable Deep-Learning Approach for Cardiac Magnetic Resonance Image Segmentation Using Image Augmentation and Attention U-NetFanwei Kong, Shawn C. Shadden. 287-296 [doi]
- Generalisable Cardiac Structure Segmentation via Attentional and Stacked Image AdaptationHongwei Li 0004, Jianguo Zhang 0001, Bjoern H. Menze. 297-304 [doi]
- Style-Invariant Cardiac Image Segmentation with Test-Time AugmentationXiaoqiong Huang, Zejian Chen, Xin Yang 0009, Zhendong Liu, Yuxin Zou, Mingyuan Luo, Wufeng Xue, Dong Ni. 305-315 [doi]
- Comparison of a Hybrid Mixture Model and a CNN for the Segmentation of Myocardial Pathologies in Delayed Enhancement MRIMarkus Hüllebrand, Matthias Ivantsits, Hannu Zhang, Peter Kohlmann, Jan-Martin Kuhnigk, Titus Kühne, Stefan O. Schönberg, Anja Hennemuth. 319-327 [doi]
- Cascaded Convolutional Neural Network for Automatic Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRIYichi Zhang. 328-333 [doi]
- Automatic Myocardial Disease Prediction from Delayed-Enhancement Cardiac MRI and Clinical InformationAna Lourenço, Eric Kerfoot, Irina Grigorescu, Cian M. Scannell, Marta Varela, Teresa Correia. 334-341 [doi]
- SM2N2: A Stacked Architecture for Multimodal Data and Its Application to Myocardial Infarction DetectionRishabh Sharma, Christoph F. Eick, Nikolaos V. Tsekos. 342-350 [doi]
- A Hybrid Network for Automatic Myocardial Infarction Segmentation in Delayed Enhancement-MRISen Yang, Xiyue Wang. 351-358 [doi]
- Efficient 3D Deep Learning for Myocardial Diseases SegmentationKhawla Brahim, Abdul Qayyum, Alain Lalande, Arnaud Boucher, Anis Sakly, Fabrice Mériaudeau. 359-368 [doi]
- Deep-Learning-Based Myocardial Pathology DetectionMatthias Ivantsits, Markus Hüllebrand, Sebastian Kelle, Stefan O. Schönberg, Titus Kühne, Anja Hennemuth. 369-377 [doi]
- Automatic Myocardial Infarction Evaluation from Delayed-Enhancement Cardiac MRI Using Deep Convolutional NetworksKibrom Berihu Girum, Youssef Skandarani, Raabid Hussain, Alexis Bozorg Grayeli, Gilles Créhange, Alain Lalande. 378-384 [doi]
- Uncertainty-Based Segmentation of Myocardial Infarction Areas on Cardiac MR ImagesRobin Camarasa, Alexis Faure, Thomas Crozier, Daniel Bos, Marleen de Bruijne. 385-391 [doi]
- Anatomy Prior Based U-net for Pathology Segmentation with AttentionYuncheng Zhou, Ke Zhang, Xinzhe Luo, Sihan Wang, Xiahai Zhuang. 392-399 [doi]
- Automatic Scar Segmentation from DE-MRI Using 2D Dilated UNet with Rotation-Based AugmentationXue Feng 0001, Christopher M. Kramer, Michael Salerno, Craig H. Meyer. 400-405 [doi]
- Classification of Pathological Cases of Myocardial Infarction Using Convolutional Neural Network and Random ForestJixi Shi, Zhihao Chen, Raphaël Couturier. 406-413 [doi]