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Medical image multi-stage classification method based on symmetry theory

A technology of medical images and classification methods, applied in the field of medical information, can solve the problems of in-depth multi-stage classification methods of medical images, etc., and achieve the effect of high accuracy and high accuracy.

Active Publication Date: 2014-12-17
HARBIN ENG UNIV
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AI Technical Summary

Problems solved by technology

The existing classification method is to classify medical images as positive abnormalities or locate abnormal positions, but the multi-stage classification method for medical images has not yet been realized.

Method used

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  • Medical image multi-stage classification method based on symmetry theory
  • Medical image multi-stage classification method based on symmetry theory
  • Medical image multi-stage classification method based on symmetry theory

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Experimental program
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Embodiment Construction

[0025] The present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

[0026] First preprocess the medical image:

[0027] 1. Extract the ROI region from each original brain CT image in the original image library;

[0028] 2. Intercept the ROI area and correct it;

[0029] 3. Calculate the trough distribution of the gray histogram in the ROI region of the image, and obtain the trough table of the gray histogram;

[0030] 4. According to the threshold value set in the valley table, the texture is extracted multiple times from the image to obtain a multi-level texture image;

[0031] 5. Finally, the multi-level texture image is normalized into an image whose size is COLUMN×ROW;

[0032] 6. Divide the image ROI area into left and right parts about the vertical line;

[0033] 7. Divide the normalized texture image into left and right parts with respect to the vertical line;

[0034] The image is segmented and stored in...

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Abstract

The invention belongs to the technical field of medical information, and particularly relates to a medical image multi-stage classification method based on a symmetry theory. The method comprises the following steps that: images to be classified provide classification requests, wherein the images to be classified need to be original medical image data; and an image preprocessing process comprises the steps of image-based modeling, multi-stage classification and result display. The concepts of weak symmetry and high symmetry provided by the invention belong to redefinition on the medical images. A weak symmetry judging algorithm and a high symmetry judging algorithm are provided for realizing the multi-stage classification of the medical images. The classification accuracy of the multi-stage classification is very high, and the direct connection and layer-by-layer deep classification is realized in each stage, so the diagnosis precision of a doctor is improved, and the diagnosis time of the doctor is shortened. The medical image classification is realized by adopting the symmetry theory, so that the medical image multi-stage classification method based on the symmetry theory has higher accuracy.

Description

technical field [0001] The invention belongs to the technical field of medical information, and in particular relates to a multi-stage classification method of medical images based on symmetry theory. Background technique [0002] Because medical images contain rich images and medical information, in recent years, data mining technology for medical images has become a hot spot in the interdisciplinary research of medicine and computer science. With the rapid development of medical digital equipment, medical information databases are widely used. The structured text information of patients and a large amount of unstructured medical image information provide rich data resources for data mining of medical images. Medical images can effectively assist physicians in detecting and locating pathological change areas and judging their benign and malignant in the diagnosis process, so they are widely used in the clinical diagnosis process. However, doctors with different knowledge ...

Claims

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Application Information

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IPC IPC(8): G06K9/62
Inventor 潘海为荣晶施韩启龙高琳琳战宇吴枰
Owner HARBIN ENG UNIV
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