This project addresses the global challenge of breast cancer, particularly in low-resource settings, by creating a pioneering mammography database. Breast cancer, identified by the World Health Organization as a leading cause of cancer death among women, often faces diagnostic and treatment resource constraints in low- and middle-income countries. To enhance early diagnosis and address educational setbacks, the project focuses on leveraging artificial intelligence (AI) technologies through a comprehensive database. Developed in collaboration with Ambra Health, a cloud-based medical image management software, the database comprises 941 mammography images from 100 anonymized cases, with 62 % including 3D images. Accessible through http://mamografia.unifesp.br, the platform facilitates a simple registration process and an advanced search system based on 169 clinical and imaging variables. The website, customizable to the user's native language, ensures data security through an automatic anonymization system. By providing high-resolution, 3D digital images and supplementary clinical information, the platform aims to promote education and research in breast cancer diagnosis, representing a significant advancement in resource-constrained healthcare environments.
Keywords: Database; Machine Learning; Mammography; Radiology information systems; Teaching materials; artificial intelligence.
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