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Automatic segmentation of the overlapping cervical cells is one of the most challenging problems in the medical image analysis. This paper presents a novel multi-step level set (LVS) method for segmenting cytoplasm and nuclei from overlapping cells in a single EDF image produced from Pap smear images of multi-layer cervical cell volumes. The first step segments the clump consisting of free or overlapping...
Overlapping cells in a medical image can affect the extraction process of cells’ characteristics as they are visually indistinguishable from each other. This paper proposes a new separation process algorithm called the radial-based cell formation (RCF) for overlapping cells. The algorithm has been tested on 160 overlapping red blood cells taken from thin blood smear images, and 26 overlapping cervical...
Fast and reliable segmentation of cervical cell nuclei is one of the crucial steps of an automated screening system that aims early detection of cervical cancer. In this paper, we propose an edge based approach using customized Laplacian of Gaussian (LoG) filter to segment free lying cell nuclei in bright-field microscope images of Pap smear. The LoG is generally employed as a second order edge detector...
Cervix cancer is the most common gynecological malignancy and second most common cancer among female in Malaysia after breast cancer. The objective of this study is to extract the size of nucleus and cytoplasm, as well as gray level values of cervical cells from ThinPrep images so that accurate value of those parameters can easily be obtained. An alternative approach of extracting features for Pap...
Pap test is probably the most common screening method for cervical cancer. In general, the test is performed by examining the cells using a microscope. While Pap test undoubtedly facilitates diagnosis, it suffers from a number of weaknesses such as blurriness as well as the effects of unwanted noises, which may lead to false diagnosis. In order to address some of these problems, this study discusses...
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