NDLI: Detection of abnormal nuclei in cervical smear images based on visual attention model

Content Provider	IEEE Xplore Digital Library
Author	Jian-Wei Zhang Min-Chao Lian Wan-Peng Wang Lin Zhu
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China (Jian-Wei Zhang; Min-Chao Lian; Wan-Peng Wang; Lin Zhu)
Abstract	A novel idea for detecting abnormal nuclei in cervical smear images is presented. The suspect cells often appear with different externals from surrounding normal ones. Therefore, we are able to find them and focus on processing them instead of segmenting all nuclei in the images. This method combines the bottom-up attention mechanism and the top-down target-driven detection method. We extract both direction and brightness features of the image and construct a saliency map which is linearly combined with the high response area detected using annular template matching method. Then, we use an inhibition-of-return as well as winner-take-all mechanism to detect the regions of interest one by one. This process will be followed by segmentation and recognition of the found nuclei. The satisfactory results on extraction and computing speed show that this model can extract the abnormal nucleus regions without processing other part of the image.
Starting Page	920
Ending Page	924
File Size	986835
Page Count	5
File Format	PDF
ISBN	9781479902606
DOI	10.1109/ICMLC.2013.6890414
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Abstracts Visualization saliency map Visual attention cervical smear image annular template matching
Content Type	Text
Resource Type	Article

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