K-means approach in tumors cell color segmentation in lab color space

Potapov, S. N.; Kulishova, N. Ye.

Публікація:
K-means approach in tumors cell color segmentation in lab color space

dc.contributor.author	Potapov, S. N.
dc.contributor.author	Kulishova, N. Ye.
dc.date.accessioned	2018-05-02T08:44:58Z
dc.date.available	2018-05-02T08:44:58Z
dc.date.issued	2016
dc.description.abstract	Digital 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.identifier.citation	Potapov 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.uri	http://openarchive.nure.ua/handle/document/4932
dc.language.iso	en	uk_UA
dc.subject	segmentation	uk_UA
dc.subject	k-means	uk_UA
dc.subject	lab color space	uk_UA
dc.subject	immunohistochemical markers	uk_UA
dc.title	K-means approach in tumors cell color segmentation in lab color space	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication