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BMEI
2009
IEEE

Cell Clumping Quantification and Automatic Area Classification in Peripheral Blood Smear Images

11 years 6 months ago
Cell Clumping Quantification and Automatic Area Classification in Peripheral Blood Smear Images
Cell enumeration in peripheral blood smears and cell are widely applied in biological and pathological practice. Not every area in the smear is appropriate for enumeration due to severe cell clumping or sparseness arising from smear preparation. The automatic selection of good areas for cell enumeration can reduce manual labor and provide objective and consistent results. However, this has been infrequently studied and it is often difficult to count the exact number of cells in the clumps. To select good areas, we do not have to do this. Instead, we measure the goodness of such areas in terms of the degree of cell spread and the degree of clumping. The later is defined based on the distances and linking strengths of local voting peaks generated in the accumulator space after multi-scale circular Hough transforms. Support vector machines are then applied to classify the image areas into good or non-good classes. We have validated our method over 4500 testing cell images and achieved 89...
Wei Xiong, S. H. Ong, Christina Kang, Joo-Hwee Lim
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2009
Where BMEI
Authors Wei Xiong, S. H. Ong, Christina Kang, Joo-Hwee Lim, Jiang Liu, Daniel Racoceanu, Kelvin Weng Chiong Foong
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