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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/45935
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dc.contributor.authorXu Silun-
dc.contributor.authorSkakun, V.-
dc.date.accessioned2021-11-18T05:46:20Z-
dc.date.available2021-11-18T05:46:20Z-
dc.date.issued2021-
dc.identifier.citationXu Silun. Comparison of Deep Learning Preprocessing Algorithms of Nuclei Segmentation on Fluorescence Immunohistology Images of Cancer Cells / Xu Silun, Skakun V. // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 168–172.ru_RU
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/45935-
dc.description.abstractImmunohistology fluorescence image analysis is an important method for cancer diagnosis. With the widespread application of convolutional neural networks in computer vision, segmentation of images of cancer cells has become an important topic in medical image analysis. Although there are many publications describing the success in application of deep learning models for segmentation of different kind of histology images, the universal algorithm is still not developed. The image preprocessing consisting in splitting images in smaller parts and normalization is important in deep learning especially when the training set is of a limited size. In this study, we compared several approaches to create the training set of a sufficient size while having a limited number of labeled whole slide immunohistology images of cancer cells. Also, we explored different normalization methods.ru_RU
dc.language.isoenru_RU
dc.publisherUIIP NASBru_RU
dc.subjectматериалы конференцийru_RU
dc.subjectconference proceedingsru_RU
dc.subjectCNNru_RU
dc.subjectmedical image analysisru_RU
dc.subjectimage preprocessingru_RU
dc.subjectimage segmentationru_RU
dc.subjectnucleus of cancer cellru_RU
dc.subjectU-Netru_RU
dc.titleComparison of Deep Learning Preprocessing Algorithms of Nuclei Segmentation on Fluorescence Immunohistology Images of Cancer Cellsru_RU
dc.typeСтатьяru_RU
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)

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