0000000000400391

AUTHOR

Christoph Rasche

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Automatic detection of cervical cells in Pap-smear images using polar transform and k-means segmentation

2016

We introduce a novel method of cell detection and segmentation based on a polar transformation. The method assumes that the seed point of each candidate is placed inside the nucleus. The polar representation, built around the seed, is segmented using k-means clustering into one candidate-nucleus cluster, one candidate-cytoplasm cluster and up to three miscellaneous clusters, representing background or surrounding objects that are not part of the candidate cell. For assessing the natural number of clusters, the silhouette method is used. In the segmented polar representation, a number of parameters can be conveniently observed and evaluated as fuzzy memberships to the non-cell class, out of …

business.industryk-means clustering02 engineering and technologyImage segmentationElectronic mail030218 nuclear medicine & medical imagingSilhouette03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringCluster (physics)Polar020201 artificial intelligence & image processingSegmentationComputer visionArtificial intelligencebusinessCluster analysisMathematics2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)
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