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Analysis method for infant brain medical computer scanning images and realization system

A technology of scanning images and analysis methods, applied in image analysis, computed tomography, computing, etc., can solve the problems of mild mental retardation, single multifractal analysis processing mode and quantitative standard, moderate mental retardation, etc.

Inactive Publication Date: 2009-09-02
JINAN UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] 1) Mild mental retardation: 55 points ≤ DQ ≤ 75 points;
[0016] 2) Moderate mental retardation: 40 points ≤ DQ ≤ 54 points;
[0017] 3) Severe mental retardation: 25 points ≤ DQ ≤ 39 points;
[0018] 4) Very severe mental retardation: DQ<25 points
The important idea of ​​"the information contained in the part is similar to the whole" contained in the chaotic fractal theory provides a powerful theoretical weapon for judging the macroscopic pathological process based on quantitative image analysis, and complements the system theory of "understanding the part from the whole" , forming a complete dialectical idea of ​​mutual unity of quantitative and qualitative. The chaos theory method has been deeply studied as a promising frontier technology at home and abroad. However, this method is currently applied to the single computer scan image of children's brain medicine. and multifractal analysis processing mode and quantification standard are still blank

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  • Analysis method for infant brain medical computer scanning images and realization system
  • Analysis method for infant brain medical computer scanning images and realization system
  • Analysis method for infant brain medical computer scanning images and realization system

Examples

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Effect test

Embodiment 1

[0094] This example illustrates the process that the method disclosed in the present invention utilizes the process of realizing the system to process with the brain medical computer scan image of a 2-year-old boy, and the working flow chart of the system is as follows Figure 12 Shown:

[0095] Step 1: scan the original image of the 2-year-old boy's brain medical computer (such as figure 1 shown), convert it to a BMP image in Windows format, and input it into this system;

[0096] The second step: use the image processing module to identify the region of interest on the image input in the first step, and get the following figure 2 the image shown;

[0097] The third step: using the image processing module, the figure 2 The image of the image is segmented by calling the neural network toolbox gatbx and BpNet based on the genetic algorithm on the matlab R2007b platform, and the image of the region of interest is obtained as image 3 shown;

[0098] Step 4: Using the imag...

Embodiment 2

[0102] as per Figure 12 The workflow shown is to analyze the brain CT images of 99 normal infants in Guangzhou Children's Hospital who were scanned in standard positions. , The comparison of the sample mean between different age groups was performed by analysis of variance, and there was a significant difference in single factor analysis (P<0.05) and factors with a P value close to 0.05, the normal value of the statistical fractal dimension index). Divide the 99 cases of infants into four groups, among which group 1 is the newborn group; group 2 is the group of ~12 months; group 3 is the group of ~24 months; group 4 is the group of ~36 months. The obtained fractal analysis results are shown in the table As shown in 1, it can be seen that the fractal dimension varies with different age groups. Among them, the normal brain fractal dimension ranges from 1.88 to 1.90 in the neonatal period, with an average of 1.8913±0.0064; 1.90, with an average value of 1.8927±0.0045; the fract...

Embodiment 3

[0113] Taking 30 cases in Guangzhou Children's Hospital as an example, the 30 cases were first evaluated by using the professional psychomotor development assessment scale of the clinical rehabilitation department. Not knowing the results of another item's assessment prior to the assessment. Each item uses a 4-level scoring method. The environment is set as a quiet, independent room with good lighting, the room temperature is controlled at 20°C-30°C, and the children's clothes are 1-2 layers. In the case of not violating the respective assessment requirements, try to arrange the same family members to be present before and after the assessment , to encourage children to perform at their best level, and the evaluation results obtained are shown in Table 5 (among them, GMFM is the Gross Motor Function Measure score, PDMS series scores are Peabody Gross Motor Development Scale (Peabody Developmental Scale) Measure cale-Gross Motor) indicators score):

[0114] table 5

[0115] ...

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Abstract

The invention provides an analysis method for infant brain medical computer scanning images and a realization system. The analysis method is to process the brain medical computer scanning images into images with prominent fractal characteristics, and then perform mathematic quantitative analysis on the images by a chaos fractal analysis method. The method is realized under Matlab R2007 through programming, utilizes chaotic neural network and fractal principles, performs serialized division, identification and fractal mode analysis on the infant brain medical computer scanning images to obtain fractal dimension quantified reference values and quantified reference values of multifractal spectrum width of normal infant brain medical computer scanning images in different age brackets, realizes clinical prediction on sick infants with intelligent disability and brain paralysis which have no typical neural image manifest characteristics by taking the reference values as a comparison standard, thoroughly changes the conventional analysis mode for the infant brain medical computer scanning images, and has high accuracy and strong repeatability compared with scoring results of the clinically widely used Gesell scale.

Description

technical field [0001] The invention relates to the technical field of medical computer scanning image processing and application, in particular to a computer scanning image analysis method and an implementation system for infant brain medicine based on chaos fractal theory. Background technique [0002] For the prediction of abnormal brain development and damage in infants (newborn to three years old), especially the prediction of intellectual disability in children, early prediction and intervention should be performed in clinical practice to improve the prognosis. At present, the evaluation of intellectual disability in children can be judged by manual scale method and according to the scoring standards; or judged according to the brain parenchyma directly reflected in the infant brain medical computer scan images (including CT and magnetic resonance MR images): [0003] 1. Scale method [0004] The scales and scoring methods commonly used in clinical practice are: [0...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00A61B6/03A61B5/055
Inventor 罗良平李鹤虹
Owner JINAN UNIVERSITY
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