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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ongun, G. Halici, U. Leblebicioglu, K. Atalay, V. Beksac, M. Beksac, S. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Electr. & Electron. Eng., Middle East Tech. Univ., Ankara, Turkey (Ongun, G.; Halici, U.; Leblebicioglu, K.) |
| Abstract | While the early diagnosis of hematopoietic system disorders is very important in hematology, it is a highly complex and time consuming task. The early diagnosis requires a lot of patients to be followed-up by experts which, in general is unfeasible because of the required number of experts. The differential blood counter (DBC) system that we have developed is an attempt to automate the task performed manually by experts in routine. In our system, the cells are segmented using active contour models (snakes and balloons), which are initialized using morphological operators. Shape based and texture based features are utilized for the classification task. Different classifiers such as k-nearest neighbors, learning vector quantization, multi-layer perceptron and support vector machine are employed. |
| Starting Page | 2583 |
| Ending Page | 2586 |
| File Size | 552683 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780372115 |
| ISSN | 1094687X |
| DOI | 10.1109/IEMBS.2001.1017309 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-10-25 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Blood Cells (biology) Neural networks Counting circuits Support vector machines Support vector machine classification Feature extraction Shape Computer vision Medical diagnostic imaging |
| Content Type | Text |
| Resource Type | Article |
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