The African Breast Imaging Dataset for Equitable Cancer Care: Protocol for an Open Mammogram and Ultrasound Breast Cancer Detection Dataset

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Abstract

IntroductionBreast cancer is one of the most common cancers globally. Its incidence in Africa has increased sharply, surpassing that in high-income countries. Mortality remains high due to late-stage diagnosis, when treatment is less effetive. We propose the first open, longitudinal breast imaging dataset from Africa comprising point-of-care ultrasound scans, mammograms, biopsy pathology, and clinical profiles to support early detection using machine learning. Methods and AnalysisWe will engage women through community outreach and train them in self-examination. Those with suspected lesions, particularly with a family history of breast cancer, will be invited to participate. A total of 100 women will undergo baseline assessment at medical centers, including clinical exams, blood tests, and mammograms. Follow-up point-of-care ultrasound scans and clinical data will be collected at 3 and 6 months, with final assessments at 9 months including mammograms. Ethics and DisseminationThe study has been approved by the Institutional Review Boards at ECUREI and the MAI Lab. Findings will be disseminated through peer-reviewed journals and scientific conferences.

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