Towards Generalized Nuclear Segmentation in Histological Images

被引:0
|
作者
Vahadane, Abhishek [1 ]
Sethi, Amit [1 ]
机构
[1] Indian Inst Technol Guwahati, Dept Elect & Elect Engn, Gauhati 781039, India
来源
2013 IEEE 13TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE) | 2013年
关键词
seeded watershed segmentation; histological images; segmentation of cell nuclei;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Computer aided diagnosis in cancer pathology (computational pathology) using histological images of biopsies is an emerging field. Segmentation of cell nuclei can be an important step in such image processing pipelines. Although seeded watershed segmentation is a simple and computationally efficient segmentation technique, it is prone to errors like over-segmentation when applied to histological images. We report specific enhancements to this technique to improve segmentation of cell nuclei in histological images. Foreground seeds were generated by fast radial symmetry transform (FRST). Otsu thresholding was used on enhanced image to estimate tentative foreground map. Background markers were computed from the tentative foreground map. False detections in the segmented output were removed by logical AND with the tentative foreground map. Using these enhancements nuclear segmentation was significantly improved on histological images (H&E stained breast and intestinal tissue images, Feulgen stained images of prostate tissues).
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页数:4
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