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Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16–18, 2020, Proceedings, Part II

Research Article

Automated Detection of Standard Image Planes in 3D Echocardiographic Images

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  • @INPROCEEDINGS{10.1007/978-3-030-67540-0_23,
        author={Wei Peng and XiaoPing Liu and Lanping Wu},
        title={Automated Detection of Standard Image Planes in 3D Echocardiographic Images},
        proceedings={Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16--18, 2020, Proceedings, Part II},
        proceedings_a={COLLABORATECOM PART 2},
        year={2021},
        month={1},
        keywords={3D ultrasound image 3D echocardiographic image Template matching Image retrieval},
        doi={10.1007/978-3-030-67540-0_23}
    }
    
  • Wei Peng
    XiaoPing Liu
    Lanping Wu
    Year: 2021
    Automated Detection of Standard Image Planes in 3D Echocardiographic Images
    COLLABORATECOM PART 2
    Springer
    DOI: 10.1007/978-3-030-67540-0_23
Wei Peng1, XiaoPing Liu2,*, Lanping Wu3
  • 1: Information Technology Support, East China Normal University
  • 2: Computer Center, East China Normal University
  • 3: Shanghai Children’s Medical Center, Shanghai Jiaotong University
*Contact email: xpliu@cc.ecnu.edu.cn

Abstract

During the diagnosis and analysis of complex congenital heart malformation, it is time-consuming and tedious for doctors to search for standard image planes by hand from among the huge amounts of patients’ three-dimensional (3D) ultrasound heart images. To relieve the laborious manual searching task for echocardiographers, especially for non-physicians, this paper focuses on the auto-detection of five standard image planes suggested by experts in the 3D echocardiographic images. Firstly, the four-chamber (4C) image plane is auto-detected by template matching, and then the other standard image planes are obtained according to their spatial relation with the 4C image plane. We have tested our methods on 28 normal and 22 abnormal datasets, and the error rates are 7.1% and 13.6%, respectively. With low computational complexity and simple operation, the method of auto-detection of standard planes in 3D echocardiographic images shows encouraging prospects of application.

Keywords
3D ultrasound image 3D echocardiographic image Template matching Image retrieval
Published
2021-01-22
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67540-0_23
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