Loading
Low-dose breast X-ray used for screening. Newer 3D versions find more cancers with fewer false alarms.
Population mammographic screening reduces breast cancer mortality by roughly 20% in screened women. Digital breast tomosynthesis (3D) improves detection in dense breasts. Contrast-enhanced mammography approaches MRI sensitivity at lower cost. AI reading (Transpara, Lunit, Mirai risk model) is being deployed at scale in Europe.
Low-energy X-rays compress and image the breast; tomosynthesis acquires multiple angles and reconstructs slices.
Nothing recorded yet: a foundation, or a gap to fill.
Dependencies are what this technology cannot be delivered without: manufacturing steps, instruments, software, upstream methods. See its full chain on the map.
A Korean AI mammography reader used in screening programmes in Sweden and Australia and cleared in the US and Europe.
A London-built breast screening AI trialled across NHS sites as a second reader, now folded into RadNet's DeepHealth after a 2024 acquisition.
The first AI cleared for 3D mammography in the US, now part of RadNet's imaging network.
The breast screening AI tested in Sweden's MASAI trial, where AI-supported reading found more cancers and nearly halved the radiologists' workload.
Screening programmes short of radiologists can read this as prospective evidence that a well-validated AI reader can take the second reader's seat without lowering cancer detection. It is a paired-reader study in one hospital, not a randomised trial, so MASAI and real-world follow-up carry the argument further.
AI can take over one reader's work in double-reading screening programmes while finding more cancers. Whether the extra cancers found are ones that would have harmed women, and whether interval cancers fall, is the question the trial's primary endpoint will answer.
The dose-response curve behind breast surveillance programmes for women irradiated for Hodgkin lymphoma as teenagers or young adults, which in several countries start at 25 or eight years after radiotherapy and use magnetic resonance imaging as well as mammography.
Query for this technology: (TITLE:"mammography" OR ABSTRACT:"mammography" OR TITLE:"digital breast tomosynthesis" OR ABSTRACT:"digital breast tomosynthesis" OR TITLE:"breast cancer screening" OR ABSTRACT:"breast cancer screening"). Results are unfiltered search hits about Mammography & tomosynthesis, not a curated reading list.
Shares Hologic, FUJIFILM Healthcare, Contrast-enhanced mammography, Hand-held and point-of-care ultrasound.
Shares Betty Ford, Nancy Brinker, Kris Hallenga, Katie Couric.
Shares Constance D. Lehman, Interval breast cancer (a cancer found between screening rounds), Mitchell D. Schnall, FUJIFILM Healthcare.
Shares Tumour size on a breast report, and why it differs from the scan, Paget disease of the nipple, Inflammatory breast cancer, Stage shift.
Shares One-stop breast clinics: imaging, biopsy and a preliminary answer in a single visit, FUJIFILM Healthcare, Phyllodes tumour of the breast, Hand-held and point-of-care ultrasound.
Shares Katie Couric, Ireland's National Screening Service, Time to Screen (New Zealand national screening), Australia's national cancer screening programs.
Shares Ducts, lobules and the terminal duct lobular unit, Tumour size on a breast report, and why it differs from the scan, Ductal carcinoma in situ (DCIS), HER2-positive breast cancer.
Shares Phyllodes tumour of the breast, Paget disease of the nipple, Inflammatory breast cancer, Ductal carcinoma in situ (DCIS).
Open-source projects that implement or serve this technology, from OnCo's own catalogue: licence and last activity as the repository reported them on the day of the fetch. Listing is not endorsement; check the licence before reuse and the validation before clinical use.
NYU's deep neural network for screening mammography interpretation, with weights and code released.
A mammography-based model of five-year breast cancer risk from MIT, validated across several countries.
Open-source software, hardware and data projects catalogued by a third party, the Open Medical Registry, that bear on this technology. Listing is not endorsement; check each project's own licence and validation before clinical use.
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Meta-repository of screening mammography classifiers
Home for the unified VICTRE pipeline for in silico breast imaging.
From the Open Medical Registry (openmedical.sh), an MIT-licensed catalogue of open-source medicine. Blurbs are one line from each registry record; every project keeps its own licence.