ABSTRACT Microwave-based breast cancer detection is a growing field that has been investigated as a potential novel method for breast cancer detection. Breast microwave sensing (BMS) systems use low-powered, non-ionizing microwave signals to interrogate the breast tissues. While some BMS systems have been evaluated in clinical trials, many challenges remain before these systems can be used as a viable clinical option, and breast phantoms (breast models) allow for rigorous and controlled experimental investigations. This dataset, the University of Manitoba Breast Microwave Imaging Dataset (UM-BMID), contains S-parameter measurements from experimental scans of MRI-derived breast phantoms, obtained with a pre-clinical breast microwave sensing system operating over 1-8 GHz. The dataset consists of measurements from over 1250 scans of a diverse array of phantoms. The phantom array consists of phantoms of various sizes and breast densities. The .stl files used to produce the 3D-printed phantoms are also included in the dataset. We hope that this dataset can serve as a resource for researchers in breast microwave sensing to evaluate signal processing, image reconstruction, and tumour detection methods. Inspiration: This dataset uploaded to U-BRITE for "AI against CANCER DATA SCIENCE HACKATHON" https://cancer.ubrite.org/hackathon-2021/ Acknowledgements Tyson Reimer, Jordan Krenkevich, Stephen Pistorius, June 16, 2021, "University of Manitoba Breast Microwave Imaging Dataset (UM-BMID)", IEEE Dataport, doi: https://dx.doi.org/10.21227/1y0z-8t98. https://ieee-dataport.org/open-access/university-manitoba-breast-microwave-imaging-dataset-um-bmid U-BRITE last update date: 07/21/2021

U-BRITE location: /data/project/ubrite/cancer-hackathon/org/ieee-dataport/university-manitoba-breast-microwave-imaging-dataset-um-bmid