Medical Imaging

The diagnostic precision of modern oncology often rests on the ability to detect skeletal metastases before they become visible on standard x-rays, yet the visual complexity of bone scintigraphy has long remained a barrier to automated interpretation. Standard artificial intelligence models trained

A mid-study hardware or software upgrade at a clinical site can silently rewrite longitudinal data by increasing the contrast-to-noise ratio, potentially masking or mimicking a drug effect. This technical volatility represents one of the most significant yet underappreciated risks in modern drug

Current clinical workflows for diagnosing hip impingement often rely on CT scans that expose patients to ionizing radiation or expensive, time-consuming MRI procedures. This persistent diagnostic hurdle has driven a multidisciplinary team of biomedical engineers and surgeons at Dalhousie University

Because the human brain possesses a limited bandwidth for conscious awareness, even the most skilled medical professionals can overlook massive anomalies if those anomalies are unexpected. This reality was vividly illustrated through a famous experiment involving twenty-four veteran radiologists

Michigan Medicine became the first United States healthcare system to successfully implement a DICOM-based digital pathology PACS within a broader enterprise imaging network. This milestone signifies a major shift where pathology is no longer treated as an isolated laboratory function but as a

Quibim's expansion into the breast oncology sector represents a strategic effort to improve patient outcomes by providing more accurate clinical predictions from MRI scans. As of 2026, healthcare providers face a significant challenge with approximately 2.3 million new breast cancer cases