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Microscopic Cell Nuclei Segmentation Based on Adaptive Attention Window

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Abstract

This paper presents an adaptive attention window (AAW)-based microscopic cell nuclei segmentation method. For semantic AAW detection, a luminance map is used to create an initial attention window, which is then reduced close to the size of the real region of interest (ROI) using a quad-tree. The purpose of the AAW is to facilitate background removal and reduce the ROI segmentation processing time. Region segmentation is performed within the AAW, followed by region clustering and removal to produce segmentation of only ROIs. Experimental results demonstrate that the proposed method can efficiently segment one or more ROIs and produce similar segmentation results to human perception. In future work, the proposed method will be used for supporting a region-based medical image retrieval system that can generate a combined feature vector of segmented ROIs based on extraction and patient data.

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Acknowledgement

This work was supported by the grant No. RTI04-01-01 from the Regional Technology Innovation Program of the Ministry of Commerce, Industry and Energy (MOCIE).

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  1. Shindang-dong Dalseo-gu, Department of Computer Engineering, Keimyung University, Daegu, 704-701, South Korea

    ByoungChul Ko, MiSuk Seo & Jae-Yeal Nam

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  1. ByoungChul Ko
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  2. MiSuk Seo
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  3. Jae-Yeal Nam
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Correspondence to ByoungChul Ko.

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Ko, B., Seo, M. & Nam, JY. Microscopic Cell Nuclei Segmentation Based on Adaptive Attention Window. J Digit Imaging 22, 259–274 (2009). https://doi.org/10.1007/s10278-008-9129-9

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  • DOI: https://doi.org/10.1007/s10278-008-9129-9

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