Feature Extraction for Medical CT Images of Sports Tear Injury
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Feature Extraction for Medical CT Images of Sports Tear Injury Qi Nie 1 & Ye-bing Zou 1 & Jerry Chun-Wei Lin 2 Accepted: 20 October 2020 # The Author(s) 2020
Abstract Analysis of medical CT images directly affects the accuracy of clinical case diagnosis. Therefore, feature extraction problem of medical CT images is extremely important. A feature extraction algorithm for medical CT images of sports tear injury is proposed. First, CT images are decomposed into a low frequency component and a series of high frequency components in different directions by wavelet fast decomposition method. The high- and low-frequency information of CT images is enhanced by wavelet layered multi-directional image enhancement algorithm, and the multi-scale enhancement for medical CT images of sports tear injury is completed. Then, edge of the enhanced CT images is extracted using an image edge extraction algorithm based on extended mathematical morphology. Finally, based on the extracted edge information of CT images, feature extraction for medical CT images of sports tear injury is completed by the NSCT-GLCM based CT image feature extraction algorithm. Research results show that the proposed algorithm effectively extracts CT image features of sports tear injury and provides auxiliary information for doctor diagnosis. Keywords Sports tear injury . Medical CT . Image feature . Extraction algorithm . Fast wavelet transform . Multi-scale enhancement
1 Introduction The first step in diagnosis and treatment of a patient is to obtain enough information about the patient’s condition [1]. Invention of the microscope is a major advancement in the development of medicine. Because it allows people to observe microscopic worlds that are previously invisible to naked eye in the form of images [2]. Medical application of X-rays allows people to observe the internal structure of human body and provide important information for doctors to diagnose the cause of diseases [3]. Computed tomography provides accurate structural information within human body and evolves from 2D to 3D. On the basis of X-ray CT, many computed tomography techniques, such as magnetic resonance tomography, positron emission tomography, and electrical impedance tomography, have been developed. Based on these existing imaging technologies, new imaging methods are constantly being developed [4]. The first * Jerry Chun-Wei Lin [email protected] 1
Physical Education Department, Jiangxi University of Traditional Chinese Medicine, Nanchan 330004, China
2
Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5063 Bergen, Norway
step in medical image imaging is to use some kind of energy to pass through the body and measure energy after interacting with the body. Mathematical methods are then used to estimate the two-dimensional and three-dimensional distribution of this energy interacting with human tissue (absorption, attenuation, nuclear magnetic perturbations, etc.) and produce images [1]. Xray computed tom
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