Skin scar image judgment method based on second harmonic image texture analysis

An image texture and second harmonic technology, applied in the intersection of pattern recognition and biomedicine, image processing field, can solve the problems of non-existent texture extraction method, texture complexity, etc., and achieve high recognition rate and diagnostic ability

Active Publication Date: 2018-02-02
FUJIAN NORMAL UNIV
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Problems solved by technology

Texture feature extraction has a good application prospect in medical image research, but due to the complexity of texture, there is no texture extraction method applicable to various medical images so far.

Method used

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  • Skin scar image judgment method based on second harmonic image texture analysis
  • Skin scar image judgment method based on second harmonic image texture analysis
  • Skin scar image judgment method based on second harmonic image texture analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068]Texture Feature Extraction and Classification Recognition of Scar Collagen Second Harmonic Image

[0069] The specific process is as follows:

[0070] Step 1. Take the collagen second harmonic images of 20 normal and 10 abnormal scars to be processed as samples, among which 8 normal and 5 abnormal scar images are randomly selected as training set samples, and the others are used as test set samples

[0071] Step 2. Convert the second harmonic images to be processed in the training set and test set into grayscale images

[0072] Such as Figure 4 (a) shows the original second harmonic image of scar collagen, and the converted grayscale image is as follows Figure 4 (b) shown.

[0073] Step 3. Use the LD-LBP method to encode the grayscale image to extract the uniformity feature. Generate LD-LBP code map and calculate LD-LBP variance V 1

[0074] The traditional LBP operator ignores the interrelationships between local textures, and cannot reflect the gray level chang...

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Abstract

The invention relates to a method for diagnosing skin scars based on second harmonic image texture analysis, comprising the following steps: dividing the image to be processed into a training set and a test set and converting it into a grayscale image; using LD-LBP on the grayscale image Encoding, get LD-LBP code map and variance V1; use Haar wavelet transform to LD-LBP code map, calculate low-frequency sub-band coefficient mean value ULL, variance Var and energy ratio Er and horizontal sub-band coefficient mean value ULH; V1, ULL, Var, Er, and ULH form the feature vector and perform Gaussian normalization; use the fuzzy K-neighbor method on the normalized feature vector; output the test set category. The invention realizes the non-destructive diagnosis of skin scars, has better recognition effect and diagnostic ability, solves the damage problem of diagnosing scars in the prior art, and helps doctors judge the types of scars and adopt reasonable treatment methods.

Description

technical field [0001] The invention belongs to the intersecting field of image processing, pattern recognition and biomedicine, and relates to a skin scar image judging method based on second harmonic image texture analysis. Background technique [0002] Scar is a general term for the appearance and histopathological changes of normal skin tissue caused by various traumas. Broadly speaking, scars are divided into two categories: physiological (normal) and pathological (abnormal) scars. Normal scars are asymptomatic and dysfunctional, but they still require treatment due to their instability, discoloration, and tendency to enlarge. Abnormal scars are mainly divided into hypertrophic scars and keloids, which not only affect the appearance, but also affect the repair of normal tissues, and even become cancerous. Different scars need to be treated in different ways. Effectively distinguishing normal and abnormal scars can help patients to carry out reasonable treatment. Scar...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46G06K9/62
Inventor 陈冠楠刘垚朱小钦陈荣黄祖芳胡恒阳蔡坚勇吴怡林居强冯尚源
Owner FUJIAN NORMAL UNIV
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