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Cartilage recognition method and recognition system in medical imaging

A medical image and recognition method technology, applied in the field of medical image recognition, can solve the problem of low adaptability of cartilage recognition, achieve the effect of improving recognition accuracy and improving recognition efficiency

Active Publication Date: 2021-05-11
北京灵医灵科技有限公司
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Problems solved by technology

[0011] In view of the above problems, an embodiment of the present invention provides a cartilage recognition method and recognition system in medical images to solve the technical problem of low adaptability of existing recognition methods to cartilage recognition

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  • Cartilage recognition method and recognition system in medical imaging
  • Cartilage recognition method and recognition system in medical imaging
  • Cartilage recognition method and recognition system in medical imaging

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Embodiment Construction

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer and clearer, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0044] In one embodiment of the present invention, the cartilage recognition method in medical images is as follows: figure 1 shown. exist figure 1 Among them, the embodiment of the present invention includes:

[0045] Step 100: Preprocessing the grayscale image to obtain a corresponding gradient image.

[0046] The preprocessing can obtain the quantization of a single type of information in the grayscale image, fo...

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Abstract

The invention provides a cartilage recognition method and a recognition system in medical images, and solves the technical problem of low adaptability of the existing recognition methods to cartilage recognition. The method includes: preprocessing the grayscale image to obtain a corresponding gradient image; generating the first edge recognition and the second edge recognition in the gradient image according to the first edge recognition and the second edge recognition respectively formed to form The exact tissue contour is formed in the gradient image according to the first edge recognition and the second edge recognition; and the three-dimensional contour of the cartilage tissue is formed according to the variation trend among the tissue contours. The automatic processing and classification of sudden edge formation using single quantitative information improves the accuracy of tissue edge recognition. Different contour generation methods are used for verification to avoid overfitting, so that the cartilage tissue can realize automatic segmentation of the subject, accurate contour positioning and automatic three-dimensional modeling in the grayscale image, effectively improving the recognition efficiency of professional human recognition resources.

Description

technical field [0001] The invention relates to the technical field of medical image recognition, in particular to a cartilage recognition method and recognition system in medical images. Background technique [0002] In the prior art, in MRI (Magnetic Resonance Imaging, nuclear magnetic resonance imaging) images, the distinction between articular cartilage and cartilage surrounding tissue is blurred, its contrast is very low, and the thickness of cartilage is relatively thin, and the cartilage is seen from the image in some Parts and connective tissue are in a gray-scale connected state, which causes great difficulties for the automatic segmentation of articular cartilage. [0003] In recent researches, the research on the algorithm of automatic cartilage segmentation has been going on, and some methods for automatic or semi-automatic cartilage segmentation have also been proposed, most of which are based on statistical shape models or pattern recognition. At present, ther...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/13
CPCG06T7/0012G06T2207/30008G06T7/13
Inventor 林海晓武正强
Owner 北京灵医灵科技有限公司
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