FhP-AICOS’ extensive knowledge on image processing and machine learning applied to health care is now being leveraged to build a new solution to tackle cervical cancer, by making screening in low-resource areas easier and less costly.


Known for its work in the field ICT applied to health care in low-resource areas, FhP-AICOS is once again looking to revolutionize prevention in healthcare, this time by tackling cervical cancer.

Approximately 88% of cervical cancer cases are diagnosed in low-resource countries, where very few resources are allocated to prevention and treatment, despite there being sufficient scientific evidence to conclude that screening would result in significant reductions in incidence and mortality. In fact, screening tests such as the conventional Pap Smear or Liquid-based Cytology (LBC) have been responsible for a 50% decrease in cervical cancer deaths.

As screening is essential to prevent this disease, technology can be critical to improving screening rates, by making the exam more accessible.

This is the aim of a new project which FhP-AICOS is about to kick off, titled CLARE – Computer-Aided Cervical Cancer Screening, is being developed together with INESC TEC (Institute for Systems and Computer Engineering, Technology and Science). The goal is to create a novel framework that can be used as a Decision Support System (DSS) for the screening of cervical cancer.

The proposed solution will couple colposcopy and LBC diagnosis methods to computer vision and machine-learning approaches, in order to create a DSS system that can be easily integrated in the conventional clinical workflow, proven to be cost-effective, and produces accurate results.

This solution will build on background knowledge of other projects, such as MalariaScope, a mobile-based solution that provides an effective pre-diagnosis of malaria. Researchers will work with FhP-AICOS’ µSmartScope prototype, making it suitable for the  acquisition of smears images, as well as develop a companion mobile app to acquire microscopic images autonomously, and develop an image processing and analysis module to detect malignant cells.

With this project, FhP-AICOS’ researchers hope to contribute to minimizing unnecessary incidences and deaths related to cervical cancer by creating an intuitive and useful technology-based solution, capable of facilitating diagnosis, and thus, prevention.