A review of computational methods applied for identification and quantification of atherosclerotic plaques in images

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Danilo Samuel Jodas (Author) FEUP; Aledir Silveira Pereira (Author) Other; João Manuel R. S. Tavares (Author) FEUP

Journal

Title: Expert Systems with Applications

Vol. 46 No. 10.1016/j.eswa.2015.10.016

Pages: 1-14

ISSN: 0957-4174

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 38 Citations

ISI Web of Science

Scopus - 53 Citations

INSPEC

Scientific classification

FOS: Engineering and technology

CORDIS: Technological sciences

Other information

Authenticus ID: P-00G-T4E

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14