An automated differential blood count system

Ongun G., Halici U., Leblebicioglu K., Atalay V., Beksac M., Beksac S.

23rd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, İstanbul, Turkey, 25 - 28 October 2001, vol.23, pp.2583-2586 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 23
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.2583-2586
  • Keywords: differential blood counter, cell recognition, active contours, snakes, neural networks, support vector machine, RECOGNITION, SNAKE
  • Middle East Technical University Affiliated: Yes


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.