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 in | Applied Mechanics and Materials Vol. 530-531; no. Advances in Measurements and Information Technologies; pp. 297 - 300 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Zurich
Trans Tech Publications Ltd
01.02.2014
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| Subjects | |
| Online Access | Get full text |
| ISBN | 3038350397 9783038350392 |
| ISSN | 1660-9336 1662-7482 1662-7482 |
| DOI | 10.4028/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. |
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| 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 |
| Author_xml | – givenname: Guo Yun surname: Zhang fullname: Zhang, Guo Yun email: 55039952@qq.com organization: Hunan Institute of Science and Technology : Department of Information and Communication Engineering – givenname: Long Yuan surname: Guo fullname: Guo, Long Yuan email: 29312917@qq.com organization: Hunan Institute of Science and Technology : Department of Information and Communication Engineering – givenname: Shuai surname: Yuan fullname: Yuan, Shuai email: 11393832@qq.com organization: Hunan Institute of Science and Technology : Department of Information and Communication Engineering – givenname: Jian Hui surname: Wu fullname: Wu, Jian Hui email: 441631070@qq.com organization: Hunan Institute of Science and Technology : Department of Information and Communication Engineering |
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| Copyright | 2014 Trans Tech Publications Ltd Copyright Trans Tech Publications Ltd. Feb 2014 |
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| DOI | 10.4028/www.scientific.net/AMM.530-531.297 |
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| 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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