Abstract
The purpose of this project is to prepare image data set to develop AI systems to serve screening and diagnosis of breast cancer research field. Whereas early detection could have a positive impact on decreasing mortality, as this could offer more options for successful intervention and therapies to reduce the chance of malignant and metastatic progression. Six students, one research technologist, and one consultant in radiology collected the images and the patients' information. The images extracted from three imaging modalities: the Hologic 3D Mammography, Philips and Super Sonic ultrasound Machines, and GE and Philips machines for MRI. The cases were graded by a trained radiologist. A total of 3085 DICOM format images have collected for the period between 2008 - 2020 for 890 females patients ages 18 to 85. The largest portion in the data is dedicated for mammograms (51.3%), and then ultrasound (31.7%), and MRI exams (17%). There were 593 malignant cases while the benign cases were 2492 cases. The diagnosis was confirmed by biopsy technique after mammogram and ultrasound exams. The data will be continually collected in the future to serve the artificial intelligence research field and the public health community. The updated information about the data will be available on: https://kaimrc.med.sa/?page_id=11767072