Analysis methods of imaging data of central nervous system tumors

A tumor imaging and central nervous system technology, applied in the field of medical imaging, can solve the problem of inaccurate central nervous system tumors and achieve the effect of improving accuracy

Active Publication Date: 2022-02-15
XIANGYA HOSPITAL CENT SOUTH UNIV
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  • Description
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  • Application Information

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Problems solved by technology

[0006] Based on this, it is necessary to provide an analysis method for central nervous system tumor image data to solve the technical problem of inaccurate judgment of central nervous system tumors purely from medical images

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  • Analysis methods of imaging data of central nervous system tumors
  • Analysis methods of imaging data of central nervous system tumors
  • Analysis methods of imaging data of central nervous system tumors

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Embodiment Construction

[0025] In order to make the above objects, features and advantages of the present invention more comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described here, and those skilled in the art can make similar improvements without departing from the connotation of the present invention, so the present invention is not limited by the specific implementations disclosed below.

[0026] In one embodiment of the present invention, a classification method for central nervous system tumor image data is provided, combining figure 1 ,include:

[0027] T1. Obtaining the imaging data of the central nervous system tumor;

[0028] T2. Use the LASSO algorithm to autom...

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Abstract

The present invention relates to a method for analyzing image data of central nervous system tumors, comprising: S1, obtaining the image data of central nervous system tumors; S2, automatically extracting the features in the image data by using the LASSO algorithm, and analyzing the features Perform linear combination to obtain the first classification probability, and use the first classification probability as the first classification dimension; S3, generate several decision trees based on the random forest algorithm according to the characteristics, and then obtain the second classification probability according to the decision tree, Using the second classification probability as a second classification dimension; S4. Using the first classification dimension and the second classification dimension as a first two-dimensional feature, obtaining a third classification probability based on a two-dimensional SVM algorithm, and using the The third classification probability is used as the first classification result, combined with this analysis method to improve the accuracy of central nervous system tumor shadow classification.

Description

technical field [0001] The invention relates to the field of medical imaging, in particular to a method for analyzing image data of central nervous system tumors. Background technique [0002] Central nervous system tumor is a clinically common tumor, but due to the particularity of the site, high tumor invasiveness, high recurrence rate, and high drug resistance to traditional radiotherapy and chemotherapy, despite the continuous advancement of surgery, radiotherapy, and chemotherapy techniques, The relevant clinical treatment effects at home and abroad have progressed very slowly in the past 30 years. With the advancement of information technology, medical imaging data is showing an explosive growth trend. How to use these data systematically and comprehensively, continuously innovate life science theory and technology, study the mechanism of its occurrence, development and treatment resistance, and further explore new effective treatment methods. It has become a new top...

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Application Information

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IPC IPC(8): G16H30/20G16H50/20G06V10/764G06K9/62
CPCG16H30/20G16H50/20G06F18/2411
Inventor 王中杰李学军易小平王苟思义张晓金
Owner XIANGYA HOSPITAL CENT SOUTH UNIV
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