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 ...

Then, it uses that knowledge to create new, artificial image-mask pairs to augment a small dataset of real examples. A segmentation model is trained using both.

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 ...

To address this issue, we propose a region uncertainty estimation framework for Computed Tomography (CT) image segmentation using noisy labels. Specifically, we propose a sample-stratified training ...

Promptable image segmentation Despite using a backbone that is 3× smaller and being trained on only 1% of SA-1B, our lightly semi-supervised UnSAM+ surpasses the fully-supervised SAM in promptable ...

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.

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.