Abstract: Foundation models for interactive segmentation in 2D natural images and videos have sparked significant interest in building 3D foundation models for medical imaging. However, the domain ...

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, ...

Assessing the risk of radiation-induced hematologic cancer from medical imaging in children and adolescents might support informed decisions on the use of imaging. We followed a retrospective cohort ...

The American Medical Association has released new medical codes for 2026 amid a growing debate about whether the medical group may have too much influence over the healthcare coding system. The AMA ...

This project leverages U-Net for lung region segmentation and CNN for cancer classification using CT scan images. It aims to enhance lung cancer detection accuracy through deep learning techniques.

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

Scientists have created an AI tool that could help doctors identify diseases quickly and accurately using only a small number of medical images. Credit: Victoria Kotlyarchuk/iStock A new artificial ...