Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...

Researchers from Science Tokyo develop a Multi-scale Hessian-enhanced Patch-based Neural Network Model for Segmentation of Liver Tumor from CT Scans. Liver cancer is the sixth most common cancer ...

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 ...

Crop segmentation, the process of identifying crop regions in images, is fundamental to agricultural monitoring tasks such as yield prediction, pest detection, and growth assessment. Traditional ...

A new technical paper titled “A Universal AI-Powered Segmentation Model for PCBA and Semiconductor” was published by researchers at Nordson Corporation. “This paper introduces a novel universal deep ...

In this episode of The Wiley Contracting Chronicles, hosts Jordan Ross and Brooke DeLoatch discuss the growing trend of pharmacy benefit segmentation among health plans. They outline three emerging ...

One reason I've been underwhelmed by AI is that companies consistently frame it as a solution to every problem under the sun. That's why Meta's new Segment Anything Model (SAM 2) is so intriguing to ...