Mammogram Mastery: A Robust Dataset for Breast Cancer Detection and Medical Education

Published: 16 April 2024| Version 1 | DOI: 10.17632/fvjhtskg93.1
, Nariman Muhamad Aziz


This dataset presents a comprehensive data comprising breast cancer images collected from patients, encompassing two distinct sets: one from individuals diagnosed with breast cancer and another from those without the condition. The dataset is meticulously curated, vetted, and classified by specialist clinicians, ensuring its reliability and accuracy for research and educational purposes. Hailing from Iraq-Sulaymaniyah, the dataset offers a unique perspective on breast cancer prevalence and characteristics in the region. With 745 original images and 9,685 augmented images, this dataset provides a rich resource for training and evaluating deep learning algorithms aimed at breast cancer detection. The dataset's inclusion of augmented X-rays offers enhanced versatility for algorithm development and educational initiatives. This dataset holds immense potential for advancing medical research, aiding in the development of innovative diagnostic tools, and fostering educational opportunities for medical students interested in breast cancer detection and diagnosis.



Sulaimani Polytechnic University, University of Halabja, University of Human Development


Medical Education, Image Processing, Breast Cancer, Mammography, X-Ray, Early Cancer Detection, Deep Learning