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ORCID8th STACOM@MICCAI 2017: Quebec City, QC, Canada
- Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair A. Young, Olivier Bernard:
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers. Lecture Notes in Computer Science 10663, Springer 2018, ISBN 978-3-319-75540-3
Regular Papers
- Esther Puyol-Antón
, Matthew Sinclair, Bernhard Gerber, Mihaela Silvia Amzulescu, Hélène Langet, Mathieu De Craene, Paul Aljabar, Julia A. Schnabel, Paolo Piro, Andrew P. King:
Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion. 3-11 - Ilkay Öksüz, Rohan Dharmakumar, Sotirios A. Tsaftaris:
Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI. 12-20 - Antong Chen, Tian Zhou, Ilknur Icke, Sarayu Parimal, Belma Dogdas, Joseph Forbes, Smita Sampath, Ansuman Bagchi, Chih-Liang Chin:
Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images. 21-31 - Cheng Jin, Heng Yu, Jianjiang Feng, Lei Wang, Jiwen Lu, Jie Zhou:
Left Atrial Appendage Neck Modeling for Closure Surgery. 32-41 - Cheng Jin, Heng Yu, Jianjiang Feng, Lei Wang, Jiwen Lu, Jie Zhou:
Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT. 42-50 - Susana Merino-Caviedes, Lucilio Cordero-Grande, M. Teresa Sevilla-Ruiz, Ana Revilla-Orodea, M. Teresa Pérez Rodríguez, César Palencia de Lara, Marcos Martín-Fernández, Carlos Alberola-López:
Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm. 51-59 - Mia Mojica, Mihaela Pop, Maxime Sermesant, Mehran Ebrahimi:
Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts. 60-69
ACDC Challenge
- Clément Zotti, Zhiming Luo, Olivier Humbert, Alain Lalande, Pierre-Marc Jodoin:
GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation. 73-81 - Irem Cetin, Gerard Sanroma, Steffen E. Petersen, Sandy Napel, Oscar Camara, Miguel Ángel González Ballester, Karim Lekadir:
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI. 82-90 - Elias Grinias, Georgios Tziritas:
Fast Fully-Automatic Cardiac Segmentation in MRI Using MRF Model Optimization, Substructures Tracking and B-Spline Smoothing. 91-100 - Jelmer M. Wolterink, Tim Leiner, Max A. Viergever, Ivana Isgum:
Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images. 101-110 - Christian F. Baumgartner, Lisa M. Koch, Marc Pollefeys, Ender Konukoglu:
An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation. 111-119 - Fabian Isensee, Paul F. Jaeger, Peter M. Full, Ivo Wolf, Sandy Engelhardt, Klaus H. Maier-Hein:
Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features. 120-129 - Jay Patravali, Shubham Jain, Sasank Chilamkurthy:
2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation. 130-139 - Mahendra Khened, Alex Varghese, Ganapathy Krishnamurthi:
Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis Using Random Forest. 140-151 - Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng:
Class-Balanced Deep Neural Network for Automatic Ventricular Structure Segmentation. 152-160 - Yeonggul Jang, Yoonmi Hong, Seongmin Ha, Sekeun Kim, Hyuk-Jae Chang:
Automatic Segmentation of LV and RV in Cardiac MRI. 161-169 - Marc-Michel Rohé, Maxime Sermesant, Xavier Pennec:
Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net. 170-177
MM-WHS Challenge
- Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng:
3D Convolutional Networks for Fully Automatic Fine-Grained Whole Heart Partition. 181-189 - Christian Payer, Darko Stern, Horst Bischof, Martin Urschler:
Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations. 190-198 - Aliasghar Mortazi, Jeremy Burt, Ulas Bagci:
Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT. 199-206 - Gaetan Galisot, Thierry Brouard, Jean-Yves Ramel:
Local Probabilistic Atlases and a Posteriori Correction for the Segmentation of Heart Images. 207-214 - Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng:
Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing. 215-223 - Qianqian Tong, Munan Ning, Weixin Si, Xiangyun Liao, Jing Qin:
3D Deeply-Supervised U-Net Based Whole Heart Segmentation. 224-232 - Mattias P. Heinrich, Julien Oster:
MRI Whole Heart Segmentation Using Discrete Nonlinear Registration and Fast Non-local Fusion. 233-241 - Chunliang Wang, Örjan Smedby:
Automatic Whole Heart Segmentation Using Deep Learning and Shape Context. 242-249 - Guanyu Yang, Chenchen Sun, Yang Chen, Lijun Tang, Huazhong Shu, Jean-Louis Dillenseger:
Automatic Whole Heart Segmentation in CT Images Based on Multi-atlas Image Registration. 250-257
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