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Content Provider | IEEE Xplore Digital Library |
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Author | Hachaj, T. Ogiela, M.R. |
Copyright Year | 2012 |
Abstract | In this article the authors propose the neural network (NN) classifier for identification of brain perfusion abnormality type and its localization in CBF and CBV dynamic brain perfusion maps. The approach is based on comparison of average values of CBF or CBV (obtained for healthy brain) with mean CBF or CBV values measured in symmetric regions of interests (ROI) in left and right hemisphere for diagnosed patient. The proposed NN was validated on set of 31 CBF and CBV medical images acquired from 30 different adult patients (man and woman) with suspicious of is chemia / stroke. The use of NN enables not only to recognize the localization and type of perfusion abnormality but also to quantify the uncertainty of automatic diagnosis. |
Starting Page | 52 |
Ending Page | 57 |
File Size | 648331 |
Page Count | 6 |
File Format | |
ISBN | 9781467313285 |
DOI | 10.1109/IMIS.2012.15 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-07-04 |
Publisher Place | Italy |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Dynamic brain perfusion Computed tomography Neurons Automatic diagnosis support system Artificial neural networks Neural network Perfusion abnormality classification Lesions Biological neural networks Blood flow Biomedical imaging |
Content Type | Text |
Resource Type | Article |
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