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|標題:||IMAGE SEGMENTATION BASED ON EDGE DETECTION AND REGION GROWING FOR THINPREP-CERVICAL SMEAR||作者:||Lin, C.H.
|關鍵字:||ThinPrep-cervical smear;epithelial cell;detection;segmentation;edge;contour;region growing;algorithm;watersheds||Project:||International Journal of Pattern Recognition and Artificial Intelligence||期刊/報告no：:||International Journal of Pattern Recognition and Artificial Intelligence, Volume 24, Issue 7, Page(s) 1061-1089.||摘要:||
This study has developed an object detection and segmentation technique for processing cytoplasm and cell nucleus on ThinPrep-cervical smear images at various magnifications. Both edge detection techniques and region growing for adaptive threshold were applied to a segment cell nucleus, a cytoplasm, and backgrounds using a cervical cell image. To validate the accuracy and feasibility of the proposed method, we took a variety of cervical cell images to perform a series of experiments. The images were of superficial cells, intermediate cells, and abnormal cells, with each taken from ThinPrep smears at various magnifications. The results indicate that the proposed method can automatically segment cell nucleus and cytoplasm regions while accurately extracting object contours. These results can serve as a reference for examiners of cell pathologies.
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