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| Content Provider | PubMed Central |
|---|---|
| Author | Yamasaki, Toshihiko Chen, Tsuhan Hirai, Toshinori Murakami, Ryuji |
| Copyright Year | 2013 |
| Abstract | Differentiating lymphomas and glioblastomas is important for proper treatmentplanning. A number of works have been proposed but there are still some problems. Forexample, many works depend on thresholding a single feature value, which is susceptible tonoise. In other cases, experienced observers are required to extract the feature values or toprovide some interactions with the system. Even if experts are involved, interobservervariance becomes another problem. In addition, most of the works use only one or a fewslice(s) because 3D tumor segmentation is time consuming. In this paper, we propose a tumor classification system that analyzes the luminancedistribution of the whole tumor region. Typical cases are classified by the luminance rangethresholding and the apparent diffusion coefficients (ADC) thresholding. Nontypical casesare classified by a support vector machine (SVM). Most of the processing elements aresemiautomatic. Therefore, even novice users can use the system easily and get the sameresults as experts. The experiments were conducted using 40 MRI datasets. The classification accuracyof the proposed method was 91.1% without the ADC thresholding and 95.4% with the ADCthresholding. On the other hand, the baseline method, the conventional ADC thresholding,yielded only 67.5% accuracy. |
| Related Links | http://dx.doi.org/10.1155/2013/619658 |
| Starting Page | 619658 |
| File Format | |
| ISSN | 1748670X |
| e-ISSN | 17486718 |
| Journal | Computational and Mathematical Methods in Medicine |
| Volume Number | 2013 |
| Language | English |
| Publisher | Hindawi Publishing Corporation |
| Publisher Date | 2013-01-01 |
| Access Restriction | Open |
| Rights Holder | Hindawi Publishing Corporation |
| Subject Keyword | Biochemistry, Genetics and Molecular Biology(all) Modelling and Simulation Immunology and Microbiology(all) Applied Mathematics Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology Modeling and Simulation |
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