A major focus of clinical imaging workflow is disease diagnosis and management, leading to medical imaging datasets strongly tied to specific clinical objectives. This scenario has led to the ...

President Donald Trump’s doctor said in a memo released by the White House on Monday that his October medical imaging was of his cardiovascular and abdominal systems and that both showed “perfectly ...

Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...

BOSTON & SYDNEY--(BUSINESS WIRE)--Harrison.ai today announced the Harrison.ai Open Platform, a new paradigm that eliminates platform fees and enables single-integration access to multiple AI vendors.

DURHAM, N.C., Oct. 14, 2025 /PRNewswire/ -- Levee Medical ®, a medical device company focused on improving outcomes for prostate cancer surgery patients, today announced that the American Medical ...

Abstract: Cross-domain few-shot medical image segmentation (CDFSMIS) presents the fundamental challenge of segmenting novel anatomical or tissue structures on unfamiliar medical imaging domains with ...

Abstract: In the field of medical image processing, vascular image segmentation plays a crucial role in clinical diagnosis, treatment planning, prognosis, and medical decision-making. Accurate and ...

A giant python in need of urgent medical care turned a routine treatment into a dangerous struggle. This rare encounter shows the risks vets face when saving powerful reptiles. Texts about to go out ...

Medical imaging has long been a cornerstone of modern healthcare, enabling doctors to detect diseases, monitor progress, and guide treatments. Today, the integration of machine learning is pushing the ...

Tumor segmentation in lung CT using U-Net, U-Net++ and an augmentation-enhanced U-Net. Best validation Dice: 0.807 (MSD lung dataset).