NDLI: Pseudo Color Features Extraction technique for cervical cancer of Pap smear images

Content Provider	IEEE Xplore Digital Library
Author	Sulaiman, S.N. Isa, N.A.M. Othman, N.H. Noor, N.M.
Copyright Year	2010
Description	Author affiliation: Imaging and Intelligent Systems Research Team(ISRT), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia (Sulaiman, S.N.; Isa, N.A.M.) \|\| Clinical Research Platform, School of Medical Sciences, Universiti Sains, Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia (Othman, N.H.) \|\| Electrical Engineering, Universiti Teknologi MARA, Malaysia (Noor, N.M.)
Abstract	Cervix cancer is the most common gynecological malignancy and second most common cancer among female in Malaysia after breast cancer. The objective of this study is to extract the size of nucleus and cytoplasm, as well as gray level values of cervical cells from ThinPrep images so that accurate value of those parameters can easily be obtained. An alternative approach of extracting features for Pap smear cytology images i.e., by using Seed Based Region Growing technique and Pseudo Coloring is proposed in this study. The technique is called Pseudo Color Feature Extraction (PCFE). A correlation test is applied between data extracted using the proposed algorithm and data extracted manually by cytotechnologists. The technique operates well on cervical cells images with correlation values approaching 1.0 which indicates a strong positive correlation. The strongest relationship is the size of cytoplasm with correlation factor of 0.988595 and the next strongest relationship is its gray level with correlation factor of 0.981534. Such results indicate that the proposed technique is suitable and has high capability to be used as an image extraction technique for extracting cervical cells features as well as acts as a filter and a segmentation tool. This would assist cytopathologists and cytotechnologists in the cervical cancer screening process by providing accurate value of size and gray level of nucleus and cytoplasmic features.
Starting Page	314
Ending Page	319
File Size	306556
Page Count	6
File Format	PDF
ISBN	9781424481347
e-ISBN	9781424481361
DOI	10.1109/ISDA.2010.5687247
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-29
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Correlation Pseudo Color Features Extraction (PCFE) Image color analysis Feature extraction features extraction Pap smear Data mining Pixel medical imaging Cancer cervical cells
Content Type	Text
Resource Type	Article

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