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Fuzzy SVM feedback measuring method used for target recognition of medical images

A medical image, fuzzy similarity technology, applied in the field of image processing, can solve problems such as bad, limited use, sensitive selection, etc.

Inactive Publication Date: 2011-05-11
SOUTHERN MEDICAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

However, the SVM algorithm is sensitive to the selection of positive and negative examples, and sometimes bad results will be obtained if the selection is not good.
The researchers used bagging and random sampling techniques to solve this problem. This method has requirements on the number of negative images and the dimensionality of feature vectors, which limits its use.

Method used

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  • Fuzzy SVM feedback measuring method used for target recognition of medical images
  • Fuzzy SVM feedback measuring method used for target recognition of medical images
  • Fuzzy SVM feedback measuring method used for target recognition of medical images

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Embodiment Construction

[0047] A fuzzy SVM feedback measurement method for medical image target recognition, such as figure 1 Shown include the following specific steps:

[0048] Step 1, the preprocessing step, reads medical images from the hospital PACS system, and uses Gaussian filtering to preprocess the input images to reduce the impact of noise on image processing, specifically through linear transformation (I-I min )×255 / (I max -I min ) transform the gray value of all pixels into the scope of 0~255, wherein, I is the image gray value, Imin is the minimum value of the image gray, and Imax is the maximum value of the image gray;

[0049] Step 1, performing medical image window width and window level adjustment and filtering on the medical image data in the feature database;

[0050] Step 2, extracting the hard features of the medical image processed in step 2, these hard features include grayscale histogram features, invariant rectangular shape features, Gabor texture features and direction h...

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Abstract

The invention discloses a fuzzy SVM feedback measuring method used for the target recognition of medical images, comprising the following steps: (1) regulating a window width and a window position of medical image data in a characteristic database and filtering; (2) extracting hard characteristics of the medical images processed by the step (1); (3) converting the hard characteristics extracted by the step (2) into the fuzzy characteristics which are stored into a characteristic database; (4) selecting one medical image to be compared and extracting the fuzzy characteristics of the medical image to be compared , and obtaining the fuzzy similarity of the medical image to be compared and medical images in the characteristic database, arraying the medical images in the characteristic database according to the value of the fuzzy similarity, and M images are output from high value to low value; (5) bringing the fuzzy characteristics of the M once output images into feedback treatment basedon the fuzzy similarity to calculate, calculating the similarity of the medical images to be compared and all medical images in the characteristic database, and outputting N images from high value tolow value sequentially. The feedback measuring method can effectively pick needed medical images.

Description

technical field [0001] The invention relates to an image processing method, in particular to a fuzzy SVM (Support Vector Machine, Support Vector Machine) feedback measurement method for medical image target recognition, which is suitable for medical image retrieval. Background technique [0002] With the increasingly wide application of medical digital imaging equipment in clinical practice, the technology of electronic medical records and picture archiving communication system (PACS) continues to develop, and a large amount of image data is generated every day in clinical practice (the image data of larger hospitals is more than 10G per day. many). How to effectively organize, manage and output medical images is an urgent problem to be solved. In clinical practice, in the diagnosis of undiagnosed clinical images and in the teaching browsing research, if the diagnosed image with the same content as the lesion image can be found through the output technology, the reliability...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 江少锋冯衍秋陈武凡
Owner SOUTHERN MEDICAL UNIVERSITY
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