A review of Image Analysis and Machine Learning Techniques for Automated Cervical Cancer Screening from pap-smear image

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dc.contributor.authorWasswa, William
dc.contributor.authorWare, Andrew
dc.contributor.authorBasaza-Ejiri, Annabella Habinka
dc.contributor.authorObungoloch, Johnes
dc.date.accessioned2022-11-02T08:54:13Z
dc.date.available2022-11-02T08:54:13Z
dc.date.issued2018
dc.description.abstractEarly diagnosis and classification of a cancer type can help facilitate the subsequent clinical management of the patient. Cervical cancer ranks as the fourth most prevalent cancer affecting women worldwide and its early detection provides the opportunity to help save life. To that end, automated diagnosis and classification of cervical cancer from pap-smear images has become a necessity as it enables accurate, reliable and timely analysis of the condition's progress. This paper presents an overview of the state of the art as articulated in prominent recent publications focusing on automated detection of cervical cancer from pap-smear images.en_US
dc.identifier.citationWilliam, W., Ware, A., Basaza-Ejiri, A. H., & Obungoloch, J. (2018). A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images. Computer methods and programs in biomedicine, 164, 15-22.https://doi.org/10.1016/j.cmpb.2018.05.034en_US
dc.identifier.issn0169-2607
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/5120
dc.language.isoenen_US
dc.publisherComputer methods and programs in biomedicineen_US
dc.subjectMachine learning; Medical imaging; Segmentation; Pap-smear images; Classification; Cervical cancer; Pap-smearen_US
dc.titleA review of Image Analysis and Machine Learning Techniques for Automated Cervical Cancer Screening from pap-smear imageen_US
dc.typeArticleen_US
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