Key result
Novel threshold segmentation cuts carotid artery image processing speed to 120ns.
Why the study?
Image segmentation techniques can simplify the analysis of blood vessels for cardiovascular diagnosis by improving detection of abnormalities in carotid artery images.
Automated carotid intima-media segmentation may streamline vascular analysis; leaves open clinical validation and outcome impact.
In the decade of technological advancement, the image processing technique has made it possible to save lives of several beings. The image segmentation technique is used to eliminate the complex procedures in the analysis of blood vessels for cardiovascular diagnosis. The objective of this paper is to compare the segmented intima-media interface of 2D and 3D carotid artery images and implement in Unified Technology Learning Platform. The intima-media interface has been extracted using threshold segmentation technique for both 2D and 3D images. The pre-processing of the carotid artery and speckle removing followed by morphological technique can be used in the developed segmentation algorithm with the aid of Aphelion Dev software. The segmented results of 2D and 3D carotid artery image have been implemented in Unified Technology Learning Platform which enhances the speed of processing an image as 120ns. This technique will helps to improve the appearance of ultrasound image and detects the presence of abnormalities in carotid artery earlier during the diagnosis.
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Hemalatha et al. (2016) studied Carotid artery abnormalities. Threshold segmentation technique on Unified Technology Learning Platform was evaluated on Speed of processing an image. Implementation of the threshold segmentation technique for 2D and 3D carotid artery images on the Unified Technology Learning Platform enhanced the speed of processing an image to 120ns.
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