Leukocyte Segmentation using Saliency Map and Stepwise Region-merging


The KIPS Transactions:PartB , Vol. 17, No. 3, pp. 239-248, Jun. 2010
10.3745/KIPSTB.2010.17.3.239,   PDF Download:

Abstract

Leukocyte in blood smear image provides significant information to doctors for diagnosis of patient health status. Therefore, it is necessary step to separate leukocyte from blood smear image among various blood cells for early disease prediction. In this paper, we present a saliency map and stepwise region merging based leukocyte segmentation method. Since leukocyte region has salient color and texture, we create a saliency map using these feature map. Saliency map is used for sub-image separation. Then, clustering is performed on each sub-image using mean-shift. After mean-shift is applied, stepwise region-merging is applied to particle clusters to obtain final leukocyte nucleus. The experimental results show that our system can indeed improve segmentation performance compared to previous researches with average accuracy rate of 71%.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
J. W. Gim, B. C. Ko, J. Y. Nam, "Leukocyte Segmentation using Saliency Map and Stepwise Region-merging," The KIPS Transactions:PartB , vol. 17, no. 3, pp. 239-248, 2010. DOI: 10.3745/KIPSTB.2010.17.3.239.

[ACM Style]
Ja Won Gim, Byoung Chul Ko, and Jae Yeal Nam. 2010. Leukocyte Segmentation using Saliency Map and Stepwise Region-merging. The KIPS Transactions:PartB , 17, 3, (2010), 239-248. DOI: 10.3745/KIPSTB.2010.17.3.239.