Lumen segmentation in magnetic resonance images of the carotid artery

• Type: Article in International Scientific Journal
• Date: 2016-12

Authors

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

Journal

Title: Computers in Biology and Medicine

Vol. 79

Pages: 233-242

ISSN: 0010-4825

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 3 Citations

ISI Web of Science

Scopus - 8 Citations

INSPEC

Scientific classification

CORDIS: Technological sciences

FOS: Medical and Health sciences

Other information

Authenticus ID: P-00M-6D9

DOI: 10.1016/j.compbiomed.2016.10.021

Abstract (EN): Investigation of the carotid artery plays an important role in the diagnosis of cerebrovascular events. Segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images is the first step towards evaluating any possible cardiovascular diseases like atherosclerosis. However, the automatic segmentation of the lumen is still a challenge due to the low quality of the images and the presence of other elements such as stenosis and malformations that compromise the accuracy of the results. In this article, a method to identify the location of the lumen without user interaction is presented. The proposed method uses the modified mean roundness to calculate the circularity index of the regions identified by the K-means algorithm and return the one with the maximum value, i.e. the potential lumen region. Then, an active contour is employed to refine the boundary of this region. The method achieved an average Dice coefficient of 0.78 +/- 0.14 and 0.61 +/- 0.21 in 181 3D-T1-weighted and 181 proton density-weighted MR images, respectively. The results show that this method is promising for the correct identification and location of the lumen even in images corrupted by noise.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10