Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRI

Yeonggul Jang, Sekeun Kim, Hackjoon Shim, Hyuk Jae Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Accurate quantification of left ventricle (LV) from cardiac image are valuable to evaluate ventricular function information such as stroke volume and ejection fraction. In this paper, we proposed a novel FCN architecture, which is trained in end-to-end manner, for full quantification of cardiac LV on 2D + t cine MR images. Considering 3D information as features for temporal modeling can improve performance of the model for temporal-related task. The proposed FCN with the alternate 3D-2D convolutional module addresses each sequence with assistance from adjacent sequences and shows the comparable results compared with the state-of-the-art method.

Original languageEnglish
Title of host publicationStatistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges - 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers
EditorsShuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Mihaela Pop, Jichao Zhao, Maxime Sermesant, Tommaso Mansi
PublisherSpringer Verlag
Pages476-483
Number of pages8
ISBN (Print)9783030120283
DOIs
Publication statusPublished - 2019 Jan 1
Event9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: 2018 Sep 162018 Sep 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11395 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018
CountrySpain
CityGranada
Period18/9/1618/9/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Jang, Y., Kim, S., Shim, H., & Chang, H. J. (2019). Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRI. In S. Li, K. McLeod, A. Young, K. Rhode, M. Pop, J. Zhao, M. Sermesant, & T. Mansi (Eds.), Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges - 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers (pp. 476-483). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11395 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-12029-0_51