Knee osteoarthritis course detection method based on near-infrared light

Abstract

The invention belongs to the technical field of medical sciences, and discloses a knee osteoarthritis course detection method based on near-infrared light. The knee osteoarthritis course detection method comprises the steps of processing clinic knee joint CT pictures by using an image segmentation processing technology, and remaining muscle and skeleton tissue portions and performing gray scale contrast ratio reinforcement and edge extraction; and then respectively simulating movement curves of near-infrared photons in knee joints of patients having early, medial and later stages of arthritis through analyzing optical characteristic parameters of articular cavity synovia by using the Monte Carlo method based on the processed CT pictures, fitting infrared photon emitting distribution characteristics of different courses by using the Gaussian function, and determining patient conditions by using the effective photon emitting rate and symmetric axis coordinates of the fitting function as double indexes. Experimental results show that accuracy of the method reaches more than 92%, the near-infrared detection is a nondestructive testing means, and the knee osteoarthritis course detection method has large application value in knee osteoarthritis clinic detection application.

Description

technical field [0001] The invention belongs to the technical field of medicine, and in particular relates to a method for detecting the disease course of knee osteoarthritis based on near-infrared light. Background technique [0002] Knee osteoarthritis (Osteoarthritis, OA) is a common irreversible chronic joint disease, and most of the patients are elderly people over 60 years old. With the aging of society, the incidence of knee osteoarthritis is getting higher and higher. According to domestic statistics, the incidence rate of elderly people over 65 years old is 75%, which has a great impact on the health and quality of life of middle-aged and elderly people. Because the early symptoms of knee OA are not obvious, they are often ignored by people. Once it develops to an advanced stage, it will not only seriously affect the physical and mental health of patients, but also bring a huge economic burden. The disease course tracking detection method is an extremely valuable r...

AI Technical Summary

Problems solved by technology

[0003] To sum up, the problems existing in the existing technology are: (1) it will cause radiation effects on the human body, and cannot be used as a routine physical examination item, which affects the early detection and treatment of the disease; (2) the articular cartilage and joint Changes in the composition of the cavity fluid make it impossible to detect early disease information; (3) The professional technical requirements for medical personnel are relatively high when performing imaging examinations of the knee joint and determining the condition

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