Automatic segmentation of CMRIs for LV contour detection

Research on detecting, recognising and interpreting cardiovascular magnetic resonance images (CMRIs) has started since the 1980s. Time consuming and the need of expert evaluation are the key problems in the manual tracing efforts of CMRIs in a routine investigation. CMRIs manual tracing is also depe...

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Main Authors: Amjad, Khan, Dayang Nurfatimah F, Awang Iskandar, Hamimah, Ujir, Chai, Wangyin
Format: Article
Language:English
Published: Springer Verlag 2017
Subjects:
Online Access:http://ir.unimas.my/id/eprint/14939/
http://ir.unimas.my/id/eprint/14939/2/Automatic%20segmentation.pdf
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author Amjad, Khan
Dayang Nurfatimah F, Awang Iskandar
Hamimah, Ujir
Chai, Wangyin
author_facet Amjad, Khan
Dayang Nurfatimah F, Awang Iskandar
Hamimah, Ujir
Chai, Wangyin
author_sort Amjad, Khan
building UNIMAS Institutional Repository
collection Online Access
description Research on detecting, recognising and interpreting cardiovascular magnetic resonance images (CMRIs) has started since the 1980s. Time consuming and the need of expert evaluation are the key problems in the manual tracing efforts of CMRIs in a routine investigation. CMRIs manual tracing is also dependent on image quality, and there is no one-size-fits-all MRI setting for an optimum image result. In this paper, we present an approach using 2-Standard Division (2-SD) correlation along with the Sum of Absolute Difference technique and Otsu Watershed to automatically detect the left ventricle (LV) wall and blood pool in the effort to automatically assist the assessment of cardiac function. We test the approach using the Sunnybrook Cardiac Data, a standard benchmark dataset. The results shown that the proposed method had improved the automatic detection of the epicardium and endocardium
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spelling unimas-149392022-09-29T06:12:36Z http://ir.unimas.my/id/eprint/14939/ Automatic segmentation of CMRIs for LV contour detection Amjad, Khan Dayang Nurfatimah F, Awang Iskandar Hamimah, Ujir Chai, Wangyin TK Electrical engineering. Electronics Nuclear engineering Research on detecting, recognising and interpreting cardiovascular magnetic resonance images (CMRIs) has started since the 1980s. Time consuming and the need of expert evaluation are the key problems in the manual tracing efforts of CMRIs in a routine investigation. CMRIs manual tracing is also dependent on image quality, and there is no one-size-fits-all MRI setting for an optimum image result. In this paper, we present an approach using 2-Standard Division (2-SD) correlation along with the Sum of Absolute Difference technique and Otsu Watershed to automatically detect the left ventricle (LV) wall and blood pool in the effort to automatically assist the assessment of cardiac function. We test the approach using the Sunnybrook Cardiac Data, a standard benchmark dataset. The results shown that the proposed method had improved the automatic detection of the epicardium and endocardium Springer Verlag 2017 Article PeerReviewed text en http://ir.unimas.my/id/eprint/14939/2/Automatic%20segmentation.pdf Amjad, Khan and Dayang Nurfatimah F, Awang Iskandar and Hamimah, Ujir and Chai, Wangyin (2017) Automatic segmentation of CMRIs for LV contour detection. Lecture Notes in Electrical Engineering, 398. pp. 313-319. ISSN 18761100 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992724603&doi=10.1007%2f978-981-10-1721-6_34&partnerID=40&md5=02af1bc3ac27506ed80138904d694742 DOI: 10.1007/978-981-10-1721-6_34
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Amjad, Khan
Dayang Nurfatimah F, Awang Iskandar
Hamimah, Ujir
Chai, Wangyin
Automatic segmentation of CMRIs for LV contour detection
title Automatic segmentation of CMRIs for LV contour detection
title_full Automatic segmentation of CMRIs for LV contour detection
title_fullStr Automatic segmentation of CMRIs for LV contour detection
title_full_unstemmed Automatic segmentation of CMRIs for LV contour detection
title_short Automatic segmentation of CMRIs for LV contour detection
title_sort automatic segmentation of cmris for lv contour detection
topic TK Electrical engineering. Electronics Nuclear engineering
url http://ir.unimas.my/id/eprint/14939/
http://ir.unimas.my/id/eprint/14939/
http://ir.unimas.my/id/eprint/14939/
http://ir.unimas.my/id/eprint/14939/2/Automatic%20segmentation.pdf