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- W2807855649 abstract "In the context of medical diagnosis by image analysis, segmentation is the most critical step in image processing.The problem of image segmentation has been studied for years and many methods have been suggested in theliterature. However, there is not yet any automatic method able to correctly process any type of image. In thiswork, we present an automated method for cell segmentation in Pap smear images. The automatic analysis ofPap smear images is one of the most interesting fields in medical image processing. The object of this paper is topresent the strategy of the first part of the system segmentation. It is based on a segmentation of color imagestested with different classical color spaces, namely RGB, L*a*b, HSV, and YCbCr, to select the best color spaceusing k-means clustering to separate groups of objects. The k means clustering treats each object as having alocation in space. The method is aimed at developing an automated Pap smear analysis system which can helpcytotechnologists reduce examination time in pap screening process." @default.
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- W2807855649 date "2016-01-01" @default.
- W2807855649 modified "2023-10-18" @default.
- W2807855649 title "Automatic segmentation of cervical cells in Pap smear images" @default.
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