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An automated differential blood count system
Date
2001-10-28
Author
Ongun, G
Halıcı, Uğur
Leblebicioğlu, Mehmet Kemal
Atalay, Mehmet Volkan
Beksac, M
Beksac, S
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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While the early diagnosis of hematopoietic system disorders is very important in hematolgy, 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 infeasible 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 ballons), 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.
Subject Keywords
Differential blood counter
,
Cell recognition
,
Active contours
,
Snakes
,
Neural networks
,
Support vector machine
URI
https://hdl.handle.net/11511/54580
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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G. Ongun, U. Halıcı, M. K. Leblebicioğlu, M. V. Atalay, M. Beksac, and S. Beksac, “An automated differential blood count system,” 2001, vol. 23, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54580.