Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images. For ...

MIT researchers developed an interactive, AI-based system that enables users to rapidly annotate areas of interest in new biomedical imaging datasets, without training a machine-learning model in ...

Abstract: Medical imaging plays a pivotal role in diagnosing and treating a variety of conditions, from brain abnormalities to retinal diseases. However, interpreting large volumes of imaging data ...

Abstract: CNNs have demonstrated superior performance in medical image segmentation. To overcome the limitation of only using local receptive field, previous work has attempted to integrate ...

Code is executed using Pyodide in Deno and is therefore isolated from the rest of the operating system. Under the hood, code_sandbox runs an MCP server using stdio. You can run multiple code blocks ...

A research team led by Prof. Wang Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...

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.

The deal affects 30 workers at two locations at the 40-year-old practice. ECMC launches physician-led affiliate group 2024's Largest Medical Groups: See who's at the top 2024's Largest Medical Groups: ...