Lighting Up Breast Tumors During Surgery
Researchers are developing an imaging method allowing surgeons to better ID cancerous cells in the breast tumor margins during surgery.
Category: Women’s Imaging
Women’s Imaging
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Women’s Imaging
Latest
DetectedX and GE Healthcare Enter Mammography Education Partnership
DetectedX and GE Healthcare aim to expand access to the Radiology Online Learning Platform to better detect breast lesions in mammography.
Women’s Imaging
Latest
Half of All Women Experience False Positive Mammograms After 10 Years of Annual Screening
Half of all women will experience at least one false positive mammogram over a decade of annual breast cancer screening with 3D mammography.
No Need to Delay Mammogram After COVID Vaccine
There should be no delay in screening mammograms after COVID-19 vaccination due to a swelling in the lymph nodes called lymphadenopathy, according to a new study published in the journal Radiology.
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New Path to Treat Advanced Triple-Negative Breast Cancer
A new study by researchers at Yale Cancer Center shows inhibition of the CECR2 gene prevents triple-negative breast cancer from advancing or metastasizing. The discovery is an early step in finding new therapeutics for triple-negative breast cancer, one of the most difficult disease sub-types to treat.
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Architectural Distortion on Digital Breast Tomosynthesis with Nonmalignant Pathology
According to a new study, imaging surveillance is a management alternative for architectural distortion on digital breast tomosynthesis yielding radial scar without atypia and other concordant benign pathologies without atypia at biopsy.
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iCAD’s Breast AI Platform Nabs U.S. Department of Defense Authorization to Operate
iCAD, Inc. announces that the company’s breast artificial intelligence platform was granted an Authorization to Operate from the U.S. Department of Defense.
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The First AI Breast Cancer Sleuth That Shows Its Work?
Researchers have developed an artificial intelligence platform to analyze potentially cancerous lesions in mammography scans to determine if a patient should receive an invasive biopsy. But unlike its many predecessors, the algorithm is interpretable, meaning it shows physicians exactly how it came to its conclusions.
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