Detection of carotid intima and media thicknesses based on ultrasound B-mode images clustered with Gaussian mixture model

Guiling Qi; Yufeng Zhang; Zhiyao Li; Hong Mo; Jie Chen

doi:10.1117/12.2557259

3 January 2020 Detection of carotid intima and media thicknesses based on ultrasound B-mode images clustered with Gaussian mixture model

Guiling Qi, Yufeng Zhang, Zhiyao Li, Hong Mo, Jie Chen

Author Affiliations +

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 113730Q (2020) https://doi.org/10.1117/12.2557259
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

A method based on ultrasound B-mode images clustered with the Gaussian Mixture Model (GMM) was proposed to improve the detection accuracy of intima and media thicknesses in carotid arteries. Firstly, the B-mode images were clustered based on the GMM, and the boundary between the intima and media of the vessel wall is then detected by the gray threshold algorithm to estimate the thicknesses of the inner and middle membranes. With 28 healthy subjects, the thicknesses of intima and media based on GMM cluster processing were (0.1675±0.0164) mm and (0.2278±0.0208) mm, respectively. Compared with the results based on original B-mode images of (0.1742±0.0208) mm and (0.2211±0.022) mm, the standard deviations based on GMM images were reduced by 21% and 5%, respectively. Compared with the results finely measured by two professional doctors, the mean error of intima and media thickness based on GMM images decreased by 7.5 % and 8.7%, respectively. The proposed method is helpful to provide the accurate diagnosis information for cardiovascular diseases in early stage.

Citation Download Citation

Guiling Qi, Yufeng Zhang, Zhiyao Li, Hong Mo, and Jie Chen "Detection of carotid intima and media thicknesses based on ultrasound B-mode images clustered with Gaussian mixture model", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113730Q (3 January 2020); https://doi.org/10.1117/12.2557259

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