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Automatic Active Contour-Based Segmentation and Classification of Carotid Artery Ultrasound Images

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Abstract

In this paper, we present automatic image segmentation and classification technique for carotid artery ultrasound images based on active contour approach. For early detection of the plaque in carotid artery to avoid serious brain strokes, active contour-based techniques have been applied successfully to segment out the carotid artery ultrasound images. Further, ultrasound images might be affected due to rotation, scaling, or translational factors during acquisition process. Keeping in view these facts, image alignment is used as a preprocessing step to align the carotid artery ultrasound images. In our experimental study, we exploit intima–media thickness (IMT) measurement to detect the presence of plaque in the artery. Support vector machine (SVM) classification is employed using these segmented images to distinguish the normal and diseased artery images. IMT measurement is used to form the feature vector. Our proposed approach segments the carotid artery images in an automatic way and further classifies them using SVM. Experimental results show the learning capability of SVM classifier and validate the usefulness of our proposed approach. Further, the proposed approach needs minimum interaction from a user for an early detection of plaque in carotid artery. Regarding the usefulness of the proposed approach in healthcare, it can be effectively used in remote areas as a preliminary clinical step even in the absence of highly skilled radiologists.

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Acknowledgments

This research work is supported by the Higher Education Commission of Pakistan under the indigenous Ph.D. scholarship program (17-5-4(Ps4-078)/HEC/Sch/2008/) and BK21 Postdoc Fellowship Program of South Korea. The authors would like to extend their thanks to Shifa International Hospital, Islamabad for providing data and technical support to complete this research work.

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Authors and Affiliations

  1. School of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea

    Asmatullah Chaudhry & Jin Young Kim

  2. Pattern Recognition Lab, PIEAS, P.O. Nilore, 45650, Islamabad, Pakistan

    Mehdi Hassan & Asifullah Khan

  3. HRD, PINSTECH, P.O. Nilore, 45650, Islamabad, Pakistan

    Asmatullah Chaudhry

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  1. Asmatullah Chaudhry
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  2. Mehdi Hassan
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  3. Asifullah Khan
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  4. Jin Young Kim
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Correspondence to Asmatullah Chaudhry.

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Chaudhry, A., Hassan, M., Khan, A. et al. Automatic Active Contour-Based Segmentation and Classification of Carotid Artery Ultrasound Images. J Digit Imaging 26, 1071–1081 (2013). https://doi.org/10.1007/s10278-012-9566-3

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  • DOI: https://doi.org/10.1007/s10278-012-9566-3

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