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An integrated system for the segmentation of atherosclerotic carotid plaque.
- Source :
-
IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society [IEEE Trans Inf Technol Biomed] 2007 Nov; Vol. 11 (6), pp. 661-7. - Publication Year :
- 2007
-
Abstract
- In this paper, we propose and evaluate an integrated system for the segmentation of atherosclerotic plaque in ultrasound imaging of the carotid artery based on normalization, speckle reduction filtering, and four different snakes segmentation methods. These methods are the Williams and Shah, Balloon, Lai and Chin, and the gradient vector flow (GVF) snake. The performance of the four different plaque snakes segmentation methods was tested on 80 longitudinal ultrasound images of the carotid artery using receiver operating characteristic (ROC) analysis and the manual delineations of an expert. All four methods were very satisfactory and similar in all measures evaluated, with no significant differences between them; however, the Lai and Chin snakes segmentation method gave slightly better results. Concluding, it is proposed that the integrated system investigated in this study could be used successfully for the automated segmentation of the carotid plaque.
- Subjects :
- Adult
Aged
Aged, 80 and over
Female
Humans
Male
Middle Aged
Reproducibility of Results
Sensitivity and Specificity
Systems Integration
Algorithms
Artificial Intelligence
Carotid Artery Diseases diagnostic imaging
Echocardiography, Doppler methods
Image Enhancement methods
Image Interpretation, Computer-Assisted methods
Pattern Recognition, Automated methods
Subjects
Details
- Language :
- English
- ISSN :
- 1089-7771
- Volume :
- 11
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society
- Publication Type :
- Academic Journal
- Accession number :
- 18046941
- Full Text :
- https://doi.org/10.1109/titb.2006.890019