AI – based, domain-agnostic algorithmic module minimizes human errors in clinical analysis, while setting the stage for continued innovation and a new set of tools the Company will introduce in 2021 ...

The MHSAttResDU-Net incorporates RCC for complexity control and improved generalization under varying lighting. The SSRP unit in encoder-decoder blocks reduces feature map dimensions, capturing key ...

Radiologists are beginning to use AI-based computer vision models to help speed up the laborious process of parsing medical scans. However, these models require large amounts of carefully labeled ...

In a recent study published in Nature Methods, researchers assessed a novel method for bacterial cell segmentation named Omnipose. Breakthroughs in microscopy are extremely promising for enabling ...

BELFAST, Northern Ireland--(BUSINESS WIRE)--Axial3D, a leader in medical segmentation and 3D solutions, today announced that it is the first to receive FDA clearance for an automated, AI-driven, cloud ...

Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.

Please provide your email address to receive an email when new articles are posted on . Axial3D has announced FDA clearance of its automated medical segmentation platform. Axial3D also received ...

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 ...