Computer-Aided Cervical Cancer Screening


Cervical cancer is a largely preventable disease, but worldwide it is one of the leading causes of cancer death in women, with most deaths occurring in low to middle income countries. Screening tests such as the conventional pap smear or Liquid-based Cytology (LBC) has been responsible for a 50% decrease in cervical cancer deaths.

This project aims to create a novel framework that can be used as a Decision Support System (DSS) for the screening of Cervical Cancer. The proposed solution aims to couple Colposcopy and LBC diagnosis methods with computer vision and machine-learning approaches, in order to create a DSS system that can be easily integrated in the conventional clinical flow of Cervical Cancer screening.



Develop a solution that can be effectively used for Cervical Cancer screening. This solution will be based on our background knowledge (e.g. MalariaScope) and is intended to be easily integrated in the conventional clinical flow.





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