Abstract
Automatic and accurate segmentation of Left Ventricle (LV) and Right Ventricle (RV) in cine-MRI is required to analyze cardiac function and viability. We present a fully convolutional neural network to efficiently segment LV and RV as well as myocardium. The network is trained end-to-end from scratch. Average dice scores from five-fold cross-validation on the ACDC training dataset were 0.94, 0.89, and 0.88 for LV, RV, and myocardium. Experimental results show the robustness of the proposed architecture.
| Original language | English |
|---|---|
| Title of host publication | Statistical Atlases and Computational Models of the Heart |
| Subtitle of host publication | ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers |
| Editors | Olivier Bernard, Pierre-Marc Jodoin, Xiahai Zhuang, Guang Yang, Alistair Young, Maxime Sermesant, Alain Lalande, Mihaela Pop |
| Publisher | Springer Verlag |
| Pages | 161-169 |
| Number of pages | 9 |
| ISBN (Print) | 9783319755403 |
| DOIs | |
| Publication status | Published - 2018 Jan 1 |
| Event | 8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017 - Quebec City, Canada Duration: 2017 Sep 10 → 2017 Sep 14 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10663 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017 |
|---|---|
| Country | Canada |
| City | Quebec City |
| Period | 17/9/10 → 17/9/14 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Automatic segmentation of LV and RV in cardiac MRI. / Jang, Yeonggul; Hong, Yoonmi; Ha, Seongmin; Kim, Sekeun; Chang, Hyuk-Jae.
Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers. ed. / Olivier Bernard; Pierre-Marc Jodoin; Xiahai Zhuang; Guang Yang; Alistair Young; Maxime Sermesant; Alain Lalande; Mihaela Pop. Springer Verlag, 2018. p. 161-169 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10663 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Automatic segmentation of LV and RV in cardiac MRI
AU - Jang, Yeonggul
AU - Hong, Yoonmi
AU - Ha, Seongmin
AU - Kim, Sekeun
AU - Chang, Hyuk-Jae
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Automatic and accurate segmentation of Left Ventricle (LV) and Right Ventricle (RV) in cine-MRI is required to analyze cardiac function and viability. We present a fully convolutional neural network to efficiently segment LV and RV as well as myocardium. The network is trained end-to-end from scratch. Average dice scores from five-fold cross-validation on the ACDC training dataset were 0.94, 0.89, and 0.88 for LV, RV, and myocardium. Experimental results show the robustness of the proposed architecture.
AB - Automatic and accurate segmentation of Left Ventricle (LV) and Right Ventricle (RV) in cine-MRI is required to analyze cardiac function and viability. We present a fully convolutional neural network to efficiently segment LV and RV as well as myocardium. The network is trained end-to-end from scratch. Average dice scores from five-fold cross-validation on the ACDC training dataset were 0.94, 0.89, and 0.88 for LV, RV, and myocardium. Experimental results show the robustness of the proposed architecture.
UR - http://www.scopus.com/inward/record.url?scp=85044482442&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044482442&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-75541-0_17
DO - 10.1007/978-3-319-75541-0_17
M3 - Conference contribution
AN - SCOPUS:85044482442
SN - 9783319755403
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 161
EP - 169
BT - Statistical Atlases and Computational Models of the Heart
A2 - Bernard, Olivier
A2 - Jodoin, Pierre-Marc
A2 - Zhuang, Xiahai
A2 - Yang, Guang
A2 - Young, Alistair
A2 - Sermesant, Maxime
A2 - Lalande, Alain
A2 - Pop, Mihaela
PB - Springer Verlag
ER -