Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function
Research on detecting, recognising and interpreting Cardiac MRI has started since the 1980s. The problem with manual tracing efforts hampering the adoption of cardiac MRI as routine investigation. Manual tracing is also dependent on image quality, and there is no one-size-fitsall MRI setting for...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Universiti Sains Malaysia
2016
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| Online Access: | http://ir.unimas.my/id/eprint/12434/ http://ir.unimas.my/id/eprint/12434/1/Towards%20An%20Automatic%20Segmentation%20for%20Assessment%20of%20Cardiac%20Left%20Ventricle%20Function%20%28abstract%29.pdf |
| _version_ | 1848837197325664256 |
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| author | D. N. F, Awang Iskandar Amjad, Khan |
| author_facet | D. N. F, Awang Iskandar Amjad, Khan |
| author_sort | D. N. F, Awang Iskandar |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Research on detecting, recognising and interpreting Cardiac
MRI has started since the 1980s. The problem with manual tracing efforts
hampering the adoption of cardiac MRI as routine investigation. Manual
tracing is also dependent on image quality, and there is no one-size-fitsall
MRI setting for the optimum image result. In this paper, we present
a proposed approach to automatically detect the left ventricle (LV) wall
in the effort to automatically assist the assessment of cardiac function.
Using a standard bechmark dataset, our experiments have shown that
our proposed method had effectively improve the automatic detection of
the epicardium and endocardium. |
| first_indexed | 2025-11-15T06:35:50Z |
| format | Article |
| id | unimas-12434 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:35:50Z |
| publishDate | 2016 |
| publisher | Universiti Sains Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-124342016-06-22T06:42:00Z http://ir.unimas.my/id/eprint/12434/ Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function D. N. F, Awang Iskandar Amjad, Khan R Medicine (General) Research on detecting, recognising and interpreting Cardiac MRI has started since the 1980s. The problem with manual tracing efforts hampering the adoption of cardiac MRI as routine investigation. Manual tracing is also dependent on image quality, and there is no one-size-fitsall MRI setting for the optimum image result. In this paper, we present a proposed approach to automatically detect the left ventricle (LV) wall in the effort to automatically assist the assessment of cardiac function. Using a standard bechmark dataset, our experiments have shown that our proposed method had effectively improve the automatic detection of the epicardium and endocardium. Universiti Sains Malaysia 2016 Article PeerReviewed text en http://ir.unimas.my/id/eprint/12434/1/Towards%20An%20Automatic%20Segmentation%20for%20Assessment%20of%20Cardiac%20Left%20Ventricle%20Function%20%28abstract%29.pdf D. N. F, Awang Iskandar and Amjad, Khan (2016) Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function. RoViSP, 129 (2). ISSN 978-981-10-1721-6 |
| spellingShingle | R Medicine (General) D. N. F, Awang Iskandar Amjad, Khan Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function |
| title | Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function |
| title_full | Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function |
| title_fullStr | Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function |
| title_full_unstemmed | Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function |
| title_short | Towards An Automatic Segmentation for Assessment of Cardiac Left Ventricle Function |
| title_sort | towards an automatic segmentation for assessment of cardiac left ventricle function |
| topic | R Medicine (General) |
| url | http://ir.unimas.my/id/eprint/12434/ http://ir.unimas.my/id/eprint/12434/1/Towards%20An%20Automatic%20Segmentation%20for%20Assessment%20of%20Cardiac%20Left%20Ventricle%20Function%20%28abstract%29.pdf |