Title: Computer aided detection and classification of Pap smear cell images using principal component analysis

Authors: Ponnusamy Sukumar; Samikannu Ravi

Addresses: Department of Electronics and Communication Engineering, Nandha Engineering College, Erode, Tamil Nadu 638 052, India ' Faculty of Electrical Engineering, Botswana International University of Science and Technology, Palapye, Botswana

Abstract: Pap smear is a screening methodology employed in cervix cancer detection and diagnosis. The Pap smear images of cervical region are used to detect the abnormality of the cervical cells. In this paper, the computer aided automatic detection and classification method for Pap smear cell images are proposed. The cell nucleus is segmented using watershed segmentation methodology and features are extracted from segmented cell nucleus Pap smear image. The extracted features are classified using principal component analysis method. The proposed system classifies the test Pap smear cell image into dysplastic (D), parabasal (P) and superficial (S) cell images for cervical cancer diagnosis.

Keywords: Pap smear; cell nucleus; watershed; cervical cancer; features; dysplastic; parabasal; superficial; principal component.

DOI: 10.1504/IJBIC.2018.092746

International Journal of Bio-Inspired Computation, 2018 Vol.11 No.4, pp.257 - 266

Received: 10 Sep 2015
Accepted: 01 Sep 2016
Published online: 29 Jun 2018 *

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