NDLI: Extraction and classification texture of inflammatory cells and nuclei in normal pap smear images

Content Provider	IEEE Xplore Digital Library
Author	Riana, Dwiza Widyantoro, Dwi H. Mengko, Tati L.
Copyright Year	2015
Description	Author affiliation: Information System, STMIK Nusa Mandiri, Jakarta, Indonesia (Riana, Dwiza) \|\| School of Electrical Engineering & Informatics, Institut Teknologi Bandung, Indonesia (Widyantoro, Dwi H.; Mengko, Tati L)
Abstract	The presence of inflammatory cells complicates the process of identifying the nuclei in the early detection of cervical cancer. Inflammatory cells need to be eliminated to assist pathologists in reading Pap smear slides. The texture of Grey-Level Run-Length Matrix (GLRLM) for inflammatory cells and nuclei types are investigated. The inflammatory cells and nuclei have different texture, and it can be used to differentiate them. To extract all of the features, firstly manual cropping of inflammatory cells and nuclei needs to be done. All of extracted features have been analyzed and selected by Decision Tree classifier (J48). Originally there have been eleven features in the direction of 135° which are extracted to classify cropping cells into inflammatory cells and nuclei. Then the eleven features are reduced into eight, namely low gray level run emphasis, gray level non uniformity, run length non-uniformity, long run low gray-level emphasis, short run high gray-level emphasis, short run low gray-level emphasis, long run high gray-level emphasis and run percentage based on the rule of classification. This experiment is applied into 957 cells which were from 50 images. The compositions of these cells were 122 cells of nuclei and 837 cells of inflammatory. The proposed algorithm applied to all of the cells and the result of classification by using these eight texture features obtains the sensitivity rates which show that there are still nuclei of cells that were considered as inflammatory cells. It was in accordance with the conditions of the difficulties faced by the pathologist while the specificity rate suggests that inflammatory cells detected properly and few inflammatory cells are considered as nucleus.
Starting Page	65
Ending Page	69
File Size	384262
Page Count	5
File Format	PDF
e-ISBN	9781467378000
DOI	10.1109/ICICI-BME.2015.7401336
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-02
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	GLRLM Decision Tree Instruments Gray-scale Classification algorithms Information technology Texture Cells Pap Smear Image color analysis Inflammatory cells Classification Feature extraction Decision trees
Content Type	Text
Resource Type	Article

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