Automatic segmentation of CMRIs for LV contour detection

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

[img] PDF
Automatic segmentation.pdf

Download (431kB)
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

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

Item Type: Article
Additional Information: Information, Communication and Creative Technology
Uncontrolled Keywords: Automatic segmentation, Cardiac MRI, Left ventricle, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Ibrahim
Date Deposited: 24 Jan 2017 00:51
Last Modified: 29 Sep 2022 06:12
URI: http://ir.unimas.my/id/eprint/14939

Actions (For repository members only: login required)

View Item View Item