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A system for detection of cervical precancerous in field emission scanning electron microscope images using texture features

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Journal of Innovative Optical Health Sciences 2017年第2期10卷 81-92页

作者： Yessi Jusman Siew-Cheok Ng Khairunnisa Hasikin Rahmadi Kurnia Noor Azuan Abu Osman Kean Hooi Teoh Department of Biomedical Engineering Faculty of Engineering University of Malaya50603 Kuala LumpurMalaysia Department of Informatics Engineering Faculty of Engineering Universitas A bdurrab28291 PekanbaruRiauIndonesia Department of Electrical Engineering Faculty of Engineering Andalas UniversityLimau Manis Campus25163 Padang Sumatera BaratIndonesia Department of Pathology Faculty of Medicine University of Malaya50603 Kuala LumpurMalaysia

This study develops a novel cervical precancerous detection system by using texture analysis of field emission scanning electron microscopy(FE-SEM)*** processing scheme adopted in the proposed system focused on two *** first step was to enhance cervical cell FE-SEM images in order to show the precancerous characterization indicator.A problem arises from the question of how to extract features which characterize cervical precancerous *** the first step,a preprocessing technique called intensity transformation and morphological operation(ITMO)algorithm used to enhance the quality of images was *** algo-rithm consisted of contrast stretching and morphological opening *** second step was to characterize the cervical cells to three classes,namely normal,low grade intra-epithelial squamous lesion(LSIL),and high grade intra-epithelial squamous lesion(HSIL).To differen-tiate between normal and precancerous cells of the cervical cell FE-SEM images,human papillomavirus(HPV)contained in the surface of cells were used as *** this paper,we investigated the use of texture as a tool in determining precancerous cell images based on the observation that cell images have a distinct visual *** level co-occurrences matrix(GLCM)technique was used to extract the texture *** confirm the system's perfor-mance,the system was tested using 150 cervical cell FE-SEM *** results showed that the accuracy,sensitivity and specificity of the proposed system are 95.7%,95.7%and 95.8%,respectively.

关键词： cervical cancer detection electron image image processing features extraction intelligent system.

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