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 ...

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 ...

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.

In recent years, the use of computer algorithms for identifying specific objects within images, called “image segmentation,” has become popular in medical image analysis, helping doctors diagnose ...

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 ...

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 ...

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 ...