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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Barnathan, M. Jingjing Zhang Miranda, E. Megalooikonomou, V. Faro, S. Hensley, H. Del Voile, L. Khalili, K. Gordon, J. Mohamed, F.B. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Comput. & Inf. Sci., Temple Univ., Philadelphia, PA (Barnathan, M.; Jingjing Zhang; Miranda, E.; Megalooikonomou, V.) |
| Abstract | We propose a methodology for discriminating between various types of normal and diseased brain tissue in medical images that utilizes vector quantization (VQ), an image compression technique, to extract discriminative texture features. Rather than focusing on images of the entire brain, we direct our attention to extracting local descriptors for individual regions of interest (ROIs) as determined by domain experts. After determining regions of interest, we generate a "locally optimal" codebook representing texture features of each region using the Generalized Lloyd algorithm. We then utilize the codeword usage frequency of each codeword in the codebook as a discriminative feature vector for the region it represents. Finally, we compare k- nearest neighbor, neural network, support vector machine, and decision tree-based classification approaches using the Histogram Model (HM) distance metric. Combined T1 and T2 classification accuracies in mice averaged 89% under certain experimental settings, indicating that our approach may assist radiologists and surgeons in determining disease margins and tissue homogeneity and support construction of brain atlases and pathology models. |
| Starting Page | 464 |
| Ending Page | 467 |
| File Size | 250950 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424420025 |
| DOI | 10.1109/ISBI.2008.4541033 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-14 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Magnetic resonance Brain Biomedical imaging Vector quantization Image coding Feature extraction Frequency Nearest neighbor searches Biological neural networks Support vector machines Brain Images Texture descriptors Pattern analysis Classification |
| Content Type | Text |
| Resource Type | Article |
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