Abstract
Images obtained by Intravascular ultrasound (IVUS) technology play a key role in detecting the lining of blood vessels. However, IVUS images are not clear enough usually, it is difficult to detect the inner wall of the blood vessels. It further affects the diagnosis results. In view of this situation, we first applies the pseudo-color enhancement algorithm to enhance the image; Second, the images were dichotomized by Support Vector Classification (SVC), and the images were divided into internal and external parts; then Hough gradient transform based on Canny operator is applied to detect the inner wall of blood vessels. The proposed method was applied to detect 100 frames of IVUS images and compared with the actual judgment results of doctors. The detection results showed that the detection results of blood vessel lining in 97 frames were consistent with the doctors’ judgment results, and the detection accuracy could reach 97%. Experimental results show that the method can effectively highlight the characteristics of the inner wall of blood vessels and detect the inner wall of blood vessels. It can greatly improve the diagnostic accuracy in the actual medical process.
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Su, H., Lv, L., Xie, X., Miao, M. (2023). Study on Detection of Vascular Inner Wall with IVUS Image. In: Zhao, J. (eds) Wireless and Satellite Systems. WiSATS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 509. Springer, Cham. https://doi.org/10.1007/978-3-031-34851-8_2
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DOI: https://doi.org/10.1007/978-3-031-34851-8_2
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