Abstract
We present the METINUS (METhod of Immunohistochemical NUclei Segmentation) , which is a improved and modified version of supporting tool for pathologists from 2010. The method supports examination of immunohistochemically stained thin tissue sections from biopsy of follicular lymphoma patients. The software localizes and counts FOXP3 expression in the cells’ nuclei supporting standard procedure of diagnosis and prognosis. The algorithm performs colour separation followed by object extraction and validation. Objects with statistical parameters not in specified range are disqualified from further assessment. To calculate the statistics we use the following: three channels of RGB, three channels of Lab colour space, brown channel and three layers completed with colour deconvolution. Division of the objects is done with support of watershed and colour deconvolution algorithm. Evaluation was performed on arbitrarily chosen 20 images with moderate quality of most typical tissues. We compared results of improved method with the previous version in the context of semiautomatic, pathologist controlled, computer-aided result of quantification as reference. Comparison is based on quantity of nuclei located per image using Kendall’s tau-b correlation coefficient. It shows concordance of 0.91 between results of proposed method and reference, while with previous version it is only 0.71.
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Roszkowiak, L., Korzynska, A., Lejeune, M., Bosch, R., Lopez, C. (2016). Improvements to Segmentation Method of Stained Lymphoma Tissue Section Images. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_57
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