Image omics feature selection method based on momentum adaptive harmony search

A feature selection method and radiomics technology, applied in the field of radiomics, can solve problems such as high computational cost, reduced search efficiency and accuracy, and difficulty in considering the correlation between features, so as to enhance robustness and accelerate convergence Effect

Pending Publication Date: 2022-05-13
ZHEJIANG UNIV OF TECH
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  • Claims
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Problems solved by technology

The current feature selection methods are often difficult to consider the correlation between features, or the calculation cost is high, and feature selection is essentially an optimization problem, so it is...

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  • Image omics feature selection method based on momentum adaptive harmony search
  • Image omics feature selection method based on momentum adaptive harmony search
  • Image omics feature selection method based on momentum adaptive harmony search

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Embodiment Construction

[0031] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0032] On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0033] see Figure 1-4 , a feature selection method for radiomics based on momentum adaptive harmony ...

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Abstract

The invention discloses a radiomics feature selection method based on momentum adaptive harmony search, and belongs to the technical field of radiomics. The method comprises the following steps of: 1, checking a region of interest (ROI) of the medical image; 2, adrenal tumor CT image data containing the ROI are read; 3, extracting original image features from the read image data; 4, defining an objective function of the method for minimizing the problem; 5, initializing a harmony memory bank; 6, initializing the maximum number of iterations, the HMCR and the PAR; 7, generating a new solution j; 8, updating the harmony memory bank; and 9, repeating the steps 7-8, and outputting an optimal feature subset. According to the method, the HMCR and the PAR are dynamically adjusted, so that sinking into a local optimal solution is avoided, and the robustness of the algorithm is enhanced; the concept of momentum gradient descent is fused, and convergence is accelerated; the fitness function is adjusted, and the essence of the feature search optimization problem is better conformed.

Description

technical field [0001] The invention belongs to the technical field of radiomics, and in particular relates to a feature selection method of radiomics based on momentum adaptive harmony search. Background technique [0002] Adrenal adenoma (AA) is the most common benign tumor of the adrenal gland. It originates from the adrenal cortex. It usually has no specific clinical symptoms. It is often found accidentally in physical examination or other examinations of the chest and abdomen. Clinically, it is divided into no and no tumors according to whether the tumor has endocrine function or not. Functional adenoma and functional adenoma, most of which are non-functioning adenoma clinically. At present, according to the different CT values ​​of adenomas, 10 HU is used as the critical point, and adenomas > 10 HU are defined as fat-poor adrenal adenoma (LP-AA). Adrenal metastases (AM) are the most common malignant tumors of the adrenal glands, second only to benign AA in incidenc...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06V10/25G06V10/774G06V10/764G06K9/62
CPCG06T7/0012G06T2207/10081G06T2207/30084G06T2207/30096G06F18/24143G06F18/214
Inventor 王丽萍陆炎杰王辉叶铭滔
Owner ZHEJIANG UNIV OF TECH
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