Study of Brain Computer Aided Diagnostic System Based on CT Image

Brain computer aided diagnostic system based on CT image has been widely applied for medical clinical field, which studies image preprocessing, feature extraction and image classification diagnosis based on digital image processing technology. This paper presents system design and realization of aid...

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Published inApplied Mechanics and Materials Vol. 530-531; no. Advances in Measurements and Information Technologies; pp. 297 - 300
Main Authors Zhang, Guo Yun, Guo, Long Yuan, Yuan, Shuai, Wu, Jian Hui
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.02.2014
Subjects
Online AccessGet full text
ISBN3038350397
9783038350392
ISSN1660-9336
1662-7482
1662-7482
DOI10.4028/www.scientific.net/AMM.530-531.297

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Abstract Brain computer aided diagnostic system based on CT image has been widely applied for medical clinical field, which studies image preprocessing, feature extraction and image classification diagnosis based on digital image processing technology. This paper presents system design and realization of aided diagnostic technology for brain CT image. The dynamic grey level range of CT image is extended by adopting segmental linear stretching method at first. Then textural features of CT image are extracted based on GLCM (grey level concurrence matrix). BP neural network algorithm is used to design a classifier for textural features vector of CT image at last, which identifies normal and abnormal brain CT image. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.
AbstractList Brain computer aided diagnostic system based on CT image has been widely applied for medical clinical field, which studies image preprocessing, feature extraction and image classification diagnosis based on digital image processing technology. This paper presents system design and realization of aided diagnostic technology for brain CT image. The dynamic grey level range of CT image is extended by adopting segmental linear stretching method at first. Then textural features of CT image are extracted based on GLCM (grey level concurrence matrix). BP neural network algorithm is used to design a classifier for textural features vector of CT image at last, which identifies normal and abnormal brain CT image. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.
Author Wu, Jian Hui
Guo, Long Yuan
Yuan, Shuai
Zhang, Guo Yun
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Issue Advances in Measurements and Information Technologies
Keywords Image Classification
CT Image
Brain
Preprocessing
Computer Aided Diagnostic System
Feature Extraction
BP Neural Network Algorithm
Segmental Linear Stretching
GLCM
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SubjectTerms Algorithms
Brain
Diagnostic systems
Feature extraction
Image classification
Neural networks
Preprocessing
Title Study of Brain Computer Aided Diagnostic System Based on CT Image
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