Browsing by Author "Habinka Basaza-Ejiri, Annabella"
Now showing items 1-3 of 3
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Automated Segmentation of Nucleus, Cytoplasm and Background of Cervical Cells from Pap-smear Images using a Trainable Pixel Level Classifier
Wasswa, William; Obungoloch, Johnes; Habinka Basaza-Ejiri, Annabella; Ware, Andrew (IEEE Xplore, 2019)Abstract— Cervical cancer ranks as the fourth most prevalent cancer affecting women worldwide and its early detection provides the opportunity to help save life. Automated diagnosis of cervical cancer from pap-smear images ... -
Cervical cancer classification from Pap-smears using an enhanced fuzzy Cmeans algorithm
Wasswa, William; Ware, Andrew; Obungoloch, Johnes; Habinka Basaza-Ejiri, Annabella (Informatics in Medicine Unlocked, 2019)Globally, cervical cancer ranks as the fourth most prevalent cancer affecting women. However, it can be successfully treated if detected at an early stage. The Pap smear is a good tool for initial screening of cervical ... -
A review of Image Analysis and Machine Learning Techniques for Automated Cervical Cancer Screening from pap-smear images
Wasswa, William; Habinka Basaza-Ejiri, Annabella; Ware, Andrew; Obungoloch, Johnes (Computer methods and programs in biomedicine, 2018)Background and Objective: Early 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 ...