Abstract Seamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different ...

Background: This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual ...

Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

The long, strange story of masking and law enforcement. Credit...Photo illustration by Alex Merto Supported by By Sabrina Tavernise One of the defining images of President Trump’s second term so far ...

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 ...

Code repository for training a brain tumour U-Net 3D image segmentation model using the 'Task1 Brain Tumour' medical segmentation decathlon challenge dataset.

Abstract: Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is often degraded by speckle noise, low ...