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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Artan, Y. Xiaolei Huang |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Electr. Eng., Lehigh Univ., Bethlehem, PA (Artan, Y.) |
| Abstract | In image classification problems, especially those involving tumor or precancerous lesion, we are usually faced with the situation in which the cost of mistakenly classifying samples in one class is much higher than that of the opposite mistake in the other class. Therefore it is essential to include cost information about classes in our classification methods. This paper applies a cost-sensitive 2v-SVM classification scheme to cervical cancer images to separate diseased regions from healthy tissue. Using this method, we are able to specify a higher weight to the class that is deemed more important. To the best of our knowledge, cost-sensitive SVM based medical image classification has not been done before. We specifically target segmenting disease regions in digitized uterine cervix images in a NCI/NLM archive of 60,000 images. Our second contribution is the introduction of a multiple classifier scheme instead of the traditional single classifier model. Using the multiple classifier scheme improves significantly classification accuracy as demonstrated by our experiments. |
| Starting Page | 488 |
| Ending Page | 491 |
| File Size | 623703 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424420025 |
| DOI | 10.1109/ISBI.2008.4541039 |
| 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 | Image segmentation Image classification Costs Neoplasms Lesions Cervical cancer Support vector machines Support vector machine classification Biomedical imaging Diseases support vector machines classification cost costsensitive classifiers tissue segmentation multiple classifier system segmentation evaluation |
| Content Type | Text |
| Resource Type | Article |
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