A persistent homology-based topological loss function for multi-class CNN segmentation of cardiac MRI Nick Byrne, James Clough, Giovanni Montana, Andrew King
Automatic multiplanar CT reformatting from trans-axial into left ventricle short-axis view Marta Nuñez Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Maxime Sermesant
Graph convolutional regression of cardiac depolarization from sparse endocardial maps Felix Meister, Tiziano Passerini, Chloe Audigier, Èric Lluch, Viorel Mihalef, Hiroshi Ashikaga, Andreas Maier, Henry Halperin, Tommaso Mansi
A cartesian grid representation of left atrial appendages for deep learning-based estimation of thrombogenic risk predictors César Acebes, Xabier Morales, Oscar Camara
Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks Qiaoying Huang, Eric Chen, Hanchao Yu, Yimo Guo, Terrence Chen, Dimitris Metaxas, Shanhui Sun
Modelling Fine-rained Cardiac Motion via Spatio-temporal Graph Convolutional Networks to Boost the Diagnosis of Heart Conditions Ping Lu, Wenjia Bai, Daniel Rueckert, Alison Noble
Towards meshfree patient-specific mitral valve modeling Judit Ros, Oscar Camara, Uxio Hermida, Bart Bijnens, Hernán G. Morales
PIEMAP: Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps Thomas Grandits, Simone Pezzuto, Jolijn Lubrecht, Thomas Pock, Gernot Plank, Rolf Krause
Automatic Detection of Landmarks for Fast Cardiac MR Image Registration Mia Mojica, Mihaela Pop, Mehran Ebrahimi
Quality-aware semi-supervised learning for CMR segmentation Bram Ruijsink, Esther Puyol Anton, Ye Li, Wenjia Bai, Reza Razavi, Andrew King
Estimation of imaging biomarker’s progression in post-infarct patients using cross-sectional data Marta Nuñez Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, Maxime Sermesant
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data Meng Ye, Qiaoying Huang, DONG YANG, Pengxiang Wu, Jingru Yi, Leon Axel, Dimitris Metaxas
Shape constrained CNN for cardiac MR segmentation with simultaneous prediction of shape and pose parameters Sofie Tilborghs, Tom Dresselaers, Piet Claus, Jan Bogaert, Frederik Maes
Left atrial ejection fraction estimation using SEGANet for fully automated segmentation of CINE MRI Ana Lourenço, Eric Kerfoot, Connor Dibblin, Ebraham Alskaf, Mustafa Anjari, Anil Bharath, Andrew King, Henry Chubb, Teresa Correia, Marta Varela
Estimation of Cardiac Valve Annuli Motion with Deep Learning Eric Kerfoot, Carlos Escudero King, Tefvik Ismail, David Nordsletten, Renee Miller
4D Flow Magnetic Resonance Imaging for Left Atrial Haemodynamic Characterization and Model Calibration Xabier Morales, Jordi Mill, Gaspar Delso, Marta Sitges, Ada Doltra, Filip Loncaric, Bart Bijnens, Oscar Camara
Segmentation-free Estimation of Aortic Diameters from MRI Using Deep Learning Axel Aguerreberry, Alain Lalande, Ezequiel de la Rosa, Elmer Fernández
Histogram Matching Augmentation for Domain Adaptation with Application to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation Jun Ma
A 2-step Deep Learning method with Domain Adaptation for Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Magnetic Resonance Segmentation Jorge Corral Acero, Vaanathi Sundaresan, Nicola dinsdale, Mark Jenkinson, Vicente Grau
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information Lei Li, Veronika Zimmer, Wangbin Ding, Fuping Wu, Julia Schnabel, Xiahai Zhuang
Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer Yao Zhang, Jiawei Yang, Feng Hou, Yang Liu, Yixin Wang, Jiang Tian, Cheng Zhong, Zhiqiang He
Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation Cian Scannell, Amedeo Chiribiri, Mitko Veta
The Effect of Data Augmentation on Robustness against Domain Shifts in cMRI Segmentations Peter Full, Paul Jäger, Fabian Isensee, Klaus Maier-Hein
A deep convolutional neural network approach for the segmentation of cardiac structures from MRI sequences Adam Carscadden, Michelle Noga, Kumaradevan Punithakumar
Multi-center, Multi-vendor, and Multi-DiseaseCardiac Image Segmentation Using Scale-Independent Multi-Gate UNET Mina Essam, Dina Abdelrauof, Mustafa Elattar
Adaptive Preprocessing for Generalization in Cardiac MR Image Segmentation Firas Khader, Justus Schock, Daniel Truhn, Fabian Morsbach, Christoph Haarburger
Deidentifying MRI data domain by iterative backpropagation Mario Parreño Lara, Roberto Paredes, Alberto Albiol
A generalizable deep-learning approach for cardiac magnetic resonance image segmentation using image augmentation and attention U-Net Fanwei Kong, Shawn Shadden
Generalisable Cardiac Structure Segmentation via Attentional and Stacked Image Adaptation Hongwei Li, Jianguo Zhang, Bjoern Menze
EfficientSeg: A Simple but Efficient Solution to Myocardial Pathology Segmentation Challenge Jianpeng Zhang, Yutong Xie, Zhibin Liao, Johan Verjans, Yong Xia
Cascaded Framework with Complementary CMR Information for Myocardial Pathology Segmentation Jun Ma
Two-stage Method for Segmentation of the Myocardial Scars and Edema on Multi-sequence Cardiac Magnetic Resonance Yanfei Liu, Maodan Zhang, Qi Zhan, Dongdong Gu, Guocai Liu
Dual-path Feature Aggregation Network Combined Multi-layer Fusion for Myocardial Pathology Segmentation with Multi-sequence Cardiac MR Feiyan Li, Weisheng Li
Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling Haochuan Jiang, Chengjia Wang, Agisilaos Chartsias, Sotirios A.Tsaftaris
CMS-UNet: Cardiac Multi-task Segmentation in MRI with a U-shaped Network Weisheng Li, Linhong Wang, Sheng Qin
Dual Attention U-net for Multi-Sequence Cardiac MR Images Segmentation Hong Yu, Sen Zha, Yubin Huangfu, Chen Chen, Meng Ding, Jiangyun Li
Automatic Myocardial Scar Segmentation from Multi-Sequence Cardiac MRI using Fully Convolutional Densenet with Inception and Squeeze-Excitation Module Tewodros Weldebirhan Arega, Stephanie Bricq
Accurate Myocardial Pathology Segmentation with Residual U-Net Altunok Elif, Oksuz Ilkay
Myocardial Edema and Scar Segmentation using a Coarse-to-Fine Framework with Weighted Ensemble Shuwei Zhai, Ran Gu, Wenhui Lei, Guotai Wang
Fully automated deep learning based segmentation of normal, infarcted and edema regions from multiple cardiac MRI sequences Xiaoran Zhang, Michelle Noga, Kumaradevan Punithakumar
Exploring ensemble applications for multi-sequence myocardial pathology segmentation Markus J. Ankenbrand, David Lohr, Laura M. Schreiber
Stacked and Parallel U-Nets with Multi-Output for Myocardial Pathology Segmentation Zhou Zhao, Nicolas Boutry, ElodiePuybareau
Stacked BCDU-net with semantic CMR synthesis: application to Myocardial PathologySegmentation challenge Carlos Mart́ın-Isla, Maryam Asadi-Aghbolaghi, Polyxeni Gkontra, Victor M. Campello, Sergio Escalera, Karim Lekadir
Recognition and correction cardiac MRI orientation via multi-tasking learning and deep neural networks Ke Zhang, Xiahai Zhuang
Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI Challenge
Comparison of a Hybrid Mixture Model and a CNN for the Segmentation Myocardial Pathologies in Delayed enhancement MRI Markus Hullebrand, Matthias Ivantsits, Hannu Zhang, Peter Kohlmann, Jan-Martin Kuhnigk, Titus Kuehne,Stefan Schonberg, Anja Hennemuth
Cascaded Convolutional Neural Network for Automatic Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRI Yichi Zhang
Cascaded Framework for Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRI Jun Ma
Automatic Myocardial Disease Prediction From Delayed-Enhancement Cardiac MRI and Clinical Information Ana Lourenco, Eric Kerfoot, Irina Grigorescu, Cian M Scannell, Marta Varela, Teresa M Correia
SM2N2: A Stacked Architecture for Multimodal Data and its Application to Myocardial Infarction Detection Rishabh Sharma, Christoph F. Eick, Nikolaos V. Tsekos
A Hybrid Network for Automatic Myocardial Infarction Segmentation in Delayed Enhancement-MRI Sen Yang, Xiyue Wang
Efficient 3D deep learning for myocardial diseases segmentation Khawla Brahim, Abdul Qayyum, Alain Lalande, Arnaud Boucher, Anis Sakly, Fabrice Meriaudeau
Deep-learning-based myocardial pathology Detection Matthias Ivantsits, Markus Hullebrand, Sebastian Kelle, Titus Kuehne, Anja Hennemuth
Automatic myocardial infarction evaluation from DE-MRI using deep convolutional networks Kibrom B. Girum, Youssef Skandarani, Raabid Hussain, Alexis Bozorg-Grayeli, Gilles Crehange, Alain Lalande
Uncertainty based Segmentation of Myocardial Infarction Areas on Cardiac MR images Thomas Crozier, Alexis Faure, Daniel Bos, Marleen De Bruijne, Robin Camarasa
Anatomy Prior Based U-net for Pathology Segmentation with Attention Yuncheng Zhou, Ke Zhang, Xinzhe Luo, Sihan Wang, Xiahai Zhuang
Automatic Scar Segmentation from DE-MRI Using 2D Dilated UNet with Rotation-based Augmentation Xue Feng, Christopher M. Kramer, Michael Salerno, Craig H. Meyer
Classication of pathological cases of myocardial infarction using Convolutional Neural Network and Random Forest Jixi Shi, Zhihao Chen, Raphael Couturier
