A review of computational methods applied for identification and quantification of atherosclerotic plaques in images. (15th March 2016)
- Record Type:
- Journal Article
- Title:
- A review of computational methods applied for identification and quantification of atherosclerotic plaques in images. (15th March 2016)
- Main Title:
- A review of computational methods applied for identification and quantification of atherosclerotic plaques in images
- Authors:
- Jodas, Danilo Samuel
Pereira, Aledir Silveira
Tavares, João Manuel R.S. - Abstract:
- Highlights: A review of methodologies developed to analyze atherosclerotic plaques in images is presented. The traditional visual analysis of atherosclerotic plaques in images is introduced. The segmentation of atherosclerotic plaques in ultrasound, CT and MR images is addressed. Techniques of image processing, clustering and classification are reviewed. The effectiveness and drawbacks of each technique are discussed. Abstract: Evaluation of the composition of atherosclerotic plaques in images is an important task to determine their pathophysiology. Visual analysis is still as the most basic and often approach to determine the morphology of the atherosclerotic plaques. In addition, computer-aided methods have also been developed for identification of features such as echogenicity, texture and surface in such plaques. In this article, a review of the most important methodologies that have been developed to identify the main components of atherosclerotic plaques in images is presented. Hence, computational algorithms that take into consideration the analysis of the plaques echogenicity, image processing techniques, clustering algorithms and supervised classification used for segmentation, i.e. identification, of the atherosclerotic plaque components in ultrasound, computerized tomography and magnetic resonance images are introduced. The main contribution of this paper is to provide a categorization of the most important studies related to the segmentation of atheroscleroticHighlights: A review of methodologies developed to analyze atherosclerotic plaques in images is presented. The traditional visual analysis of atherosclerotic plaques in images is introduced. The segmentation of atherosclerotic plaques in ultrasound, CT and MR images is addressed. Techniques of image processing, clustering and classification are reviewed. The effectiveness and drawbacks of each technique are discussed. Abstract: Evaluation of the composition of atherosclerotic plaques in images is an important task to determine their pathophysiology. Visual analysis is still as the most basic and often approach to determine the morphology of the atherosclerotic plaques. In addition, computer-aided methods have also been developed for identification of features such as echogenicity, texture and surface in such plaques. In this article, a review of the most important methodologies that have been developed to identify the main components of atherosclerotic plaques in images is presented. Hence, computational algorithms that take into consideration the analysis of the plaques echogenicity, image processing techniques, clustering algorithms and supervised classification used for segmentation, i.e. identification, of the atherosclerotic plaque components in ultrasound, computerized tomography and magnetic resonance images are introduced. The main contribution of this paper is to provide a categorization of the most important studies related to the segmentation of atherosclerotic plaques and its components in images acquired by the most used imaging modalities. In addition, the effectiveness and drawbacks of each methodology as well as future researches concerning the segmentation and classification of the atherosclerotic lesions are also discussed. … (more)
- Is Part Of:
- Expert systems with applications. Volume 46(2016)
- Journal:
- Expert systems with applications
- Issue:
- Volume 46(2016)
- Issue Display:
- Volume 46, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 46
- Issue:
- 2016
- Issue Sort Value:
- 2016-0046-2016-0000
- Page Start:
- 1
- Page End:
- 14
- Publication Date:
- 2016-03-15
- Subjects:
- Stroke -- Medical imaging -- Image analysis -- Image segmentation
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2015.10.016 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7862.xml