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Evaluation of carotid intima media thickness measurement from ultrasound images

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Abstract

A third of deaths in the world are due to cardiovascular diseases [1]. Atherosclerosis is the major cause of myocardial infarction, which occurs by deposition of plaque in the coronary artery. The chance of stroke rises with the thickening of carotid artery due to the plaque. Hence, accurate measurement of the intima-media thickness is necessary for predicting the chance of stroke. The stopping criterion and active resampling are incorporated in greedy snake segmentation technique. This modified algorithm segmented and extracted the intima-media complex in the ultrasound images. The snake control points obtained from the boundary of the region of interest forms the contour and demarcates the boundary of intima-media complex. The thickness ± standard deviation and the intra-observer error values obtained by modified algorithm are in conformity with the measurements by expert. The intra-observer error values for greedy snake segmentation methods were 0.10 and 0.09 for manual snake initialization and automatic snake initialization, respectively. Shapiro–Wilk test and One-way ANOVA test explains there is no statistical difference between group means obtained from these segmentation techniques and the expert measurement. The statistical analysis proves values of the intima-media thickness obtained from both snake segmentation techniques are very close to expert measurements.

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Acknowledgements

We would like to acknowledge the help provided by Cyprus Institute of Neurology and Genetics, in Nicosia, Cyprus, for providing the image database.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, NSS College of Engineering, Palakkad, Kerala, 678008, India

    B. Smitha

  2. Electrical Engineering Department, National Institute of Technology, Calicut, Kerala, 673601, India

    Dhanraj Yadav & Paul K. Joseph

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Smitha, B., Yadav, D. & Joseph, P.K. Evaluation of carotid intima media thickness measurement from ultrasound images. Med Biol Eng Comput 60, 407–419 (2022). https://doi.org/10.1007/s11517-021-02496-7

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