Knee osteoarthritis course detection method based on near-infrared light

A knee osteoarthritis and near-infrared light technology, applied in the medical field, can solve problems such as the inability to directly change the composition of articular cartilage and joint cavity fluid, affect the early detection and treatment of the disease, and the inability to detect early disease information, etc., to achieve Great application value, sensitive and effective early judgment, and convenient disease course judgment

Inactive Publication Date: 2017-10-24
XIAMEN UNIV OF TECH
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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

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  • Knee osteoarthritis course detection method based on near-infrared light
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  • Knee osteoarthritis course detection method based on near-infrared light

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Embodiment Construction

[0050] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0051] Due to the impact of radiation, conventional computerized tomography detection methods cannot be used as routine physical examination items, which affects the early detection and treatment of diseases.

[0052] The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0053] The method for detecting the course of knee osteoarthritis based on near-infrared light provided by the embodiments of the present invention includes: combining clinical knee joint CT images with Monte Carlo method to simulate the trajectory of infrared photons inside the ...

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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...

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Application Information

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IPC IPC(8): A61B5/00
CPCA61B5/0059A61B5/4519A61B5/4528A61B5/72
Inventor 黄江茵
Owner XIAMEN UNIV OF TECH
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