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.

AttendSeg is a new neural network architecture from DarwinAI designed to perform image segmentation on low-power/capacity computing devices.

Meta's image segmentation model could have a lot of applications, including in AR and VR.

According to a blog post from Meta, SAM is an image segmentation model that can respond to text prompts or user clicks to isolate specific objects within an image.

Recently, Meta AI Research approaches a general, promptable segment anything model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B). Without a doubt, the emergence of SAM ...

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

The core technology of this patent involves segmenting the image to be encoded into foreground and background images, ...

This application note showcases how an AI-based module has been trained to analyze brightfield images for cell segmentation, allowing insights into cell proliferation and cell morphology without the ...