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Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging
Joint Authors
Yang, Fan
Xie, Hong
He, Yan
Hussain, Mubashir
Lei, Pinggui
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-26
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Free-breathing cardiac magnetic resonance (CMR) imaging has short examination time with high reproducibility.
Detection of the end-diastole and the end-systole frames of the free-breathing cardiac magnetic resonance, supplemented by visual identification, is time consuming and laborious.
We propose a novel method for automatic identification of both the end-diastole and the end-systole frames, in the free-breathing CMR imaging.
The proposed technique utilizes the convolutional neural network to locate the left ventricle and to obtain the end-diastole and the end-systole frames from the respiratory motion signal.
The proposed procedure works successfully on our free-breathing CMR data, and the results demonstrate a high degree of accuracy and stability.
Convolutional neural network improves the postprocessing efficiency greatly and facilitates the clinical application of the free-breathing CMR imaging.
American Psychological Association (APA)
Yang, Fan& He, Yan& Hussain, Mubashir& Xie, Hong& Lei, Pinggui. 2017. Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1141953
Modern Language Association (MLA)
Yang, Fan…[et al.]. Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1141953
American Medical Association (AMA)
Yang, Fan& He, Yan& Hussain, Mubashir& Xie, Hong& Lei, Pinggui. Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1141953
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141953