Lipids are difficult to detect with light microscopy. Using a new chemical labeling strategy, a Dresden-based team led by André Nadler at the Max Planck Institute of Molecular Cell Biology and ...

Compared with natural image segmentation, small sample image segmentation tasks, such as medical image segmentation and defect detection, have been less studied. Recent studies made efforts on ...

In this paper, we present UISE, a unified image segmentation framework that achieves efficient performance across various segmentation tasks, eliminating the need for multiple specialized pipelines.

New AI model can “cut out” any object within an image—and Meta is sharing the code Meta's "Segment Anything" uses AI to isolate objects on command.

Medical image segmentation has important auxiliary significance for clinical diagnosis and treatment. Most of existing medical image segmentation solutions adopt convolutional neural networks (CNNs).

Using matching strategies to reduce the size discrepancy between retinal images and laser speckle contrast images, we could further significantly improve image synthesis and segmentation performance.