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Neighborhood rough set method for feature reduction of fMRI brain function connection data

A technology of brain function connection and neighborhood rough set, which is applied in the fields of medical data mining, application, health index calculation, etc., can solve problems such as information loss, achieve strong classification and discrimination ability, ensure performance, and avoid information loss.

Pending Publication Date: 2021-03-02
BEIJING UNIV OF TECH
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  • Description
  • Claims
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Problems solved by technology

However, this theory is only suitable for discrete data. When facing continuous data, it is necessary to discretize the data, and discretization will bring serious information loss.

Method used

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  • Neighborhood rough set method for feature reduction of fMRI brain function connection data
  • Neighborhood rough set method for feature reduction of fMRI brain function connection data
  • Neighborhood rough set method for feature reduction of fMRI brain function connection data

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Embodiment Construction

[0020] The specific implementation of the present invention and detailed steps are set forth below by the disclosed real attention deficit hyperactivity disorder data set ADHD and the autism data set ABIDE (flow chart is as follows: figure 1 shown):

[0021] Step (1) fMRI data acquisition.

[0022] Two publicly available resting-state fMRI datasets for brain disorders were used in this experiment: the Attention Deficit Hyperactivity Disorder (ADHD) dataset and the Autism Brain Imaging Data Exchange (ABIDE) dataset set. ADHD includes two groups of subjects with attention deficit hyperactivity disorder (ADHD) and normal (NC), and the website is http: / / fcon\_1000.projects.nitrc.org\ / indi / adhd200; ABIDE contains autism (Autism) and normal Two groups of subjects were tested, and the access website is: http: / / fcon\_1000.projects.nitrc.org / indi / abide. The statistics related to the two datasets are shown in Table 1.

[0023] Table 1 Dataset Statistics

[0024]

[0025] Step (2...

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Abstract

The invention discloses a neighborhood rough set method for feature reduction of fMRI brain function connection data, and provides a neighborhood rough set feature reduction method combined with the fMRI brain function connection data on the basis of double-fish-swarm intelligent search and information observation neighborhood rough set theories. The method specifically comprises the following steps: acquiring resting-state fMRI data; preprocessing the fMRI data; establishing a brain function connection decision table; searching a feature subset with strong classification discrimination capability by using a double-fish swarm algorithm; under the obtained reduction feature set, realizing support vector machine classification, and measuring the feature reduction capability of the method provided by the invention according to the classification result.

Description

technical field [0001] The invention relates to a method for feature reduction of fMRI brain functional connection data, in particular to a method for feature reduction of brain functional connection based on neighborhood rough sets. Background technique [0002] Brain functional connectivity describes the dynamic correlation of neuron activities between different brain regions, and provides a new perspective for people to understand the pathological mechanism of neurological and mental diseases. In recent years, functional Magnetic Resonance Imaging (fMRI)-based brain functional connectivity classification can find important brain functional connectivity characteristics related to certain brain diseases, which is very important for understanding the pathogenesis of brain diseases, and then for early diagnosis of brain diseases. Diagnosis and treatment are of great significance, which has attracted extensive attention of researchers. However, the high-dimensional and small-...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H50/30G16H50/70A61B5/00A61B5/055
CPCG16H50/20G16H50/30G16H50/70A61B5/0042A61B5/055A61B5/0033A61B5/4064
Inventor 杨翠翠宋晓妮冀俊忠
Owner BEIJING UNIV OF TECH
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