Image segmentation is one of those deceptively simple tasks that quietly underpins much of modern computer vision. Before a self-driving car can recognize a pedestrian, before a radiologist’s AI a ...

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 ...

Medical imaging has long faced a stubborn trade-off: the filters and algorithms that clean noise out of a computed tomography ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

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 ...