Researchers have developed LMANet, a lightweight multiscale attention network that achieves high-accuracy skin-lesion ...

Research scientists in Switzerland have developed and tested a robust AI model that automatically segments major anatomic structures in MRI images, independent of sequence, according to a study ...

Training an artificial intelligence system to outline every object in a photograph usually demands thousands of painstakingly ...

As large medical imaging datasets become widely available, researchers are increasingly turning to artificial intelligence to extract useful information from scans that were never manually annotated.

Image annotation can tell a model very different things about a picture. A box can show where a car is. A polygon can follow ...

Newswise — The amount of aerial and satellite imagery captured worldwide continues to grow at an incredible pace. Yet, efficiently identifying and labeling features in these images—like roofs, cars, ...

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 ...

There are effective approaches for 2D segmentation, yet 3D cell segmentation remains a critical bottleneck due to diverse cell morphologies, low signal-to-noise ratios, and data scarcity. We introduce ...

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 ...