Intelligent Screening Systems for Cervical Cancer
Open Access
- 1 January 2014
- journal article
- review article
- Published by Hindawi Limited in The Scientific World Journal
- Vol. 2014, 1-15
- https://doi.org/10.1155/2014/810368
Abstract
Advent of medical image digitalization leads to image processing and computer-aided diagnosis systems in numerous clinical applications. These technologies could be used to automatically diagnose patient or serve as second opinion to pathologists. This paper briefly reviews cervical screening techniques, advantages, and disadvantages. The digital data of the screening techniques are used as data for the computer screening system as replaced in the expert analysis. Four stages of the computer system are enhancement, features extraction, feature selection, and classification reviewed in detail. The computer system based on cytology data and electromagnetic spectra data achieved better accuracy than other data.Keywords
Funding Information
- Ministry of Higher Education, Malaysia (M-MOHE UM.C/625/1/HIR/MOHE/14)
This publication has 83 references indexed in Scilit:
- Intelligent classification of cervical pre-cancerous cells based on the FTIR spectraAin Shams Engineering Journal, 2012
- Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regressionJournal of Clinical Epidemiology, 2010
- Active contours with selective local or global segmentation: A new formulation and level set methodImage and Vision Computing, 2009
- Detection and segmentation of cervical cell cytoplast and nucleusInternational Journal of Imaging Systems and Technology, 2009
- Shape Priors for Segmentation of the Cervix Region Within Uterine Cervix ImagesJournal of Digital Imaging, 2008
- Early detection of cervical neoplasia by Raman spectroscopyInternational Journal of Cancer, 2007
- Raman spectroscopy studies for diagnosis of cancers in human uterine cervixVibrational Spectroscopy, 2006
- Hierarchical learning architecture with automatic feature selection for multiclass protein fold classificationIEEE Transactions on Nanobioscience, 2003
- Reflectance spectroscopy for in vivo detection of cervical precancerJournal of Biomedical Optics, 2002
- Support vector machines for spam categorizationIEEE Transactions on Neural Networks, 1999