Artificial Intelligence (AI) is revolutionizing the dynamics of technological advancement in the field of medical imaging, ...
Leukemia cell detection system using advanced segmentation and a fine-tuned ResNet50 model, with a complete backend API and Streamlit-based frontend. A deep learning system that analyzes medical ...
Senate Health, Education, Labor and Pensions (HELP) Committee Chair Bill Cassidy, M.D., is doubling down on his scrutiny of the American Medical Association's (AMA's) handling of billing and claims ...
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 ...
Abstract: The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. The recent ...
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 ...
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).
1 School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China 2 School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, ...
One in 10 childhood blood cancers may result from medical imaging-associated radiation exposure. Cancer risk increased with cumulative radiation dose, ranging from 1.41 times higher to 3.59 times ...
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