2014
DOI: 10.4028/www.scientific.net/amm.626.79
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Optimal Feature Selection for Carotid Artery Image Segmentation Using Evolutionary Computation

Abstract: Atherosclerosis is hardening of arteries due to high blood pressure and high cholesterol. It causes heart attacks, stroke and peripheral vascular disease and is the major cause of death. In this paper we have attempted a method to identify the presence of plaque in carotid artery from ultrasound images. The ultrasound image is segmented using improved spatial Fuzzy c means algorithm to identify the presence of plaque in carotid artery. Spatial wavelet, Hilbert Huang Transform (HHT), Moment of Gray Level Histog… Show more

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Cited by 2 publications
(1 citation statement)
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“…Because the acquisition of label information in real-life tasks is a challenging task, so the unsupervised feature learning has attracted the attention of researchers. Correspondingly, some achievements have been presented and most of them have been applied in the field of medical health, fault detection and image analysis [12]- [14]. According to the specific learning model, these works can be categorized into two groups: unsupervised filter feature selection methods and unsupervised embedded feature selection methods.…”
Section: Introductionmentioning
confidence: 99%
“…Because the acquisition of label information in real-life tasks is a challenging task, so the unsupervised feature learning has attracted the attention of researchers. Correspondingly, some achievements have been presented and most of them have been applied in the field of medical health, fault detection and image analysis [12]- [14]. According to the specific learning model, these works can be categorized into two groups: unsupervised filter feature selection methods and unsupervised embedded feature selection methods.…”
Section: Introductionmentioning
confidence: 99%