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Breast X-ray image feature selecting method based on BFBA and ELM

A technology of image features and X-rays, applied in the field of image processing, can solve problems such as analytical method or bat algorithm easy to fall into local optimal solution, "exponential explosion", etc., to improve classification performance, improve accuracy, and achieve good results

Active Publication Date: 2017-06-13
TAIYUAN UNIV OF TECH
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Problems solved by technology

[0004] The present invention overcomes the deficiencies in the prior art, and the technical problem to be solved is to provide a feature selection method for mammary gland X-ray images, which avoids the "exponential explosion" problem encountered by the dynamic programming method, and the analytical method or bat algorithm is easy to fall into local optimal solution problem

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  • Breast X-ray image feature selecting method based on BFBA and ELM
  • Breast X-ray image feature selecting method based on BFBA and ELM
  • Breast X-ray image feature selecting method based on BFBA and ELM

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Embodiment Construction

[0050] like figure 1 , figure 2 Shown, a kind of breast X-ray image feature selection method based on BFBA and ELM of the present invention, concrete steps are as follows: the first step, collect used data set MIAS, i.e. the Mammographic Image Analysis Society, extract the mammographic image feature, and The data set is divided into a training set and a test set. The training set is used to train the extreme learning machine ELM, namely Extreme Learning Machine, to design the ELM classifier, and the test set is used to test the effectiveness of the ELM classifier;

[0051] The method adopted for extracting mammogram image features is a gray-scale co-occurrence matrix, extracting four kinds of statistical parameters: angular second-order moment, entropy, moment of inertia, correlation coefficient, and the direction of the gray-scale co-occurrence matrix is ​​0°, 45°, 90° °, 135° in four directions; first calculate the gray level co-occurrence matrix in the four directions, ta...

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Abstract

The invention provides a breast X-ray image feature selecting method based on BFBA and ELM and relates to the technical field of image processing. The method aims at avoiding the problem of exponential explosion in a dynamic programming method and the problem that an analysis method or a bat algorithm is easily caught in a locally optimal solution. According to the technical scheme, the method includes the following steps that firstly, an adopted data set MIAS is collected; secondly, BFBA parameters are set; thirdly, a bat population is initialized; fourthly, a corresponding feature subset is generated according to each bat position code; fifthly, the search pulse frequency, speed and position of each bat are updated; sixthly and seventhly, evenly distributed random numbers rand are generated; eighthly, fitness values of all the bats are ranked, and a current optimal solution and a current optimal value are found; ninthly, whether the optimal solution is changed or not is judged; tenthly, whether stagnant_count is equal to stagnant_max or not is judged; eleventhly, the fourth step to the tenth step are repeated; twelfthly, a global optimal value and a global optimal solution are output.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a mammogram X-ray image feature selection method based on Bird Flock Bat Algorithm (BFBA) and Extreme Learning Machine (Extreme Learning Machine, ELM). Background technique [0002] Breast disease is one of the common diseases in women. At the same time, the multiple and harmful effects of breast cancer seriously affect women's health and even life. Therefore, early diagnosis of breast disease is directly related to women's personal health. Especially for breast cancer, people still can't fully determine its pathogenesis. The current clinical diagnosis methods of breast cancer mainly include touch diagnosis, histological diagnosis, cytological diagnosis and imaging diagnosis. Imaging is widely used for its convenience, scientificity and relatively high operability in diagnosis. Mammography is the most common technique for early diagnosis of breast cancer. For t...

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Application Information

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IPC IPC(8): G06K9/62G06K9/46G06N3/00G06N99/00
CPCG06N3/006G06N20/00G06V10/462G06F18/24G06F18/214
Inventor 韩晓红相洁
Owner TAIYUAN UNIV OF TECH
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