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 ...

Figure. The advantages of the DDSP framework: (a) Our strategy is to make the model domain-agnostic by exposing it to numerous diverse distributions while preserving semantic information in both ...

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 ...