Abstract
Cytological analysis, specially the cell counting, is an important element in the diagnosis of many diseases. Cell segmentation, the major phase of cell counting procedure, was basically performed by intensity thresholding, feature detection, morphological filtering, region accumulation and deformable model fitting. We present in this paper an automatic method for cell counting with segmentation based on Feature Weighted Fuzzy Clustering via a Difference of Convex functions with Optimization Algorithm called DCA. This new application of our method can give promising results compared to the traditional manual analysis despite the very high cell density.
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Hoai An, L.T., Minh Tam, L., Thi Bich Thuy, N. (2013). A Novel Approach to Automated Cell Counting Based on a Difference of Convex Functions Algorithm (DCA). In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_34
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DOI: https://doi.org/10.1007/978-3-642-40495-5_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40494-8
Online ISBN: 978-3-642-40495-5
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