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FAUST, Oliver, ACHARYA, U Rajendra, SAN, Tun Ru, YEONG, Chai Hong, MOLINARI, Filippo and NG, Kwan Hoong (2016). Computer aided diagnosis of coronary artery disease, myocardial infarction and carotid atherosclerosis using ultrasound images: a review. Physica Medica, 33, 1-15.
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Abstract
The diagnosis of Coronary Artery Disease (CAD), Myocardial Infarction (MI) and carotid atherosclerosis is of paramount importance, as these cardiovascular diseases may cause medical complications and large number of death. Ultrasound (US) is a widely used imaging modality, as it captures moving images and image features correlate well with results obtained from other imaging methods. Furthermore, US does not use ionizing radiation and it is economical when compared to other imaging modalities. However, reading US images takes time and the relationship between image and tissue composition is complex. Therefore, the diagnostic accuracy depends on both time taken to read the images and experience of the screening practitioner. Computer support tools can reduce the inter-operator variability with lower subject specific expertise, when appropriate processing methods are used. In the current review, we analysed automatic detection methods for the diagnosis of CAD, MI and carotid atherosclerosis based on thoracic and Intravascular Ultrasound (IVUS). We found that IVUS is more often used than thoracic US for CAD. But for MI and carotid atherosclerosis IVUS is still in the experimental stage. Furthermore, thoracic US is more often used than IVUS for computer aided diagnosis systems.
| Item Type: | Article |
|---|---|
| Research Institute, Centre or Group - Does NOT include content added after October 2018: | Sheffield Institute of Education |
| Departments - Does NOT include content added after October 2018: | Faculty of Science, Technology and Arts > Department of Engineering and Mathematics |
| Identification Number: | https://doi.org/10.1016/j.ejmp.2016.12.005 |
| Page Range: | 1-15 |
| Depositing User: | Oliver Faust |
| Date Deposited: | 09 Dec 2016 12:13 |
| Last Modified: | 18 Mar 2021 00:53 |
| URI: | https://shura.shu.ac.uk/id/eprint/14223 |
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