Segmentation of Microscopic Images for Counting Leukocytes
Counting of leukocytes in peripheral blood is commonly used in basic clinical diagnosis. The reliable approach to count leukocytes depends on morphological assessment of cellular materials under a light microscopy. Microscopic evaluation by medical technologists is a time-consuming and stuffy job. It is of interest to apply computer-aided analysis with image processing and pattern recognition, instead of human to count leukocytes. In this paper, a novel segmentation method is developed to count leukocytes by incorporating textural information. The proposed method integrates a non-decimated (or called shift invariant) complex wavelet transform into watershed segmentation, and uses information obtained by adaptive threshold segmentation to refine the result of watershed segmentation. Experiments demonstrate that the proposed method can obtain satisfactory results in comparison with the judgments of medical technologists.
leukocyte segmentation wavelet transform watershed transform adaptive threshold
Wei Gao Yinggan Tang Xiaoli Li
Institute of Electrical Engineering Yanshan University Qinhuangdao, 066004, China
国际会议
上海
英文
2631-2634
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）