Please use this identifier to cite or link to this item: http://openarchive.nure.ua/handle/document/4932
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dc.contributor.authorPotapov, S. N.-
dc.contributor.authorKulishova, N. Ye.-
dc.date.accessioned2018-05-02T08:44:58Z-
dc.date.available2018-05-02T08:44:58Z-
dc.date.issued2016-
dc.identifier.citationPotapov S. N. K-means approach in tumors cell color segmentation in lab color space / S. N. Potapov, N. Ye. Kulishova // Бионика интеллекта. – 2016. – №1 (86). – С. 85–89.uk_UA
dc.identifier.urihttp://openarchive.nure.ua/handle/document/4932-
dc.description.abstractDigital microscope images are becoming increasingly important in the diagnosis of serious diseases such as cancer. The observations are carried out on the immunohistochemical preparations that change color under the influence of specific markers. Automatic selection of the marked areas and their analysis allows identifying the disease in its early stages. For the detection of marked areas a two-step segmentation method using k-means is proposed: on the first stage a choice of all possible marked image areas is carried out, and on the second - their partition according to the marker expression level. Segmentation is performed in the color space Lab, which allows compensating colors differences caused by marking chemical reactions variations. To evaluate the expression level using - lightness. The marker expression level is evaluated by one of the color space coordinates - lightness L.uk_UA
dc.language.isoenuk_UA
dc.subjectsegmentationuk_UA
dc.subjectk-meansuk_UA
dc.subjectlab color spaceuk_UA
dc.subjectimmunohistochemical markersuk_UA
dc.titleK-means approach in tumors cell color segmentation in lab color spaceuk_UA
dc.typeArticleuk_UA
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