A Lawrence Technological University graduate student originally from Kazakhstan is helping redefine precision in robotic ...

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 ...

Abstract: Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Convolutional Neural Networks ...

Ultralytics Inc., a developer of computer vision models, today announced that it has raised $30 million in funding. Elephant VC led the Series A round with participation from SquareOne. Ultralytics ...

DINOv3 represents a major leap in computer vision: its frozen universal backbone and SSL approach enable researchers and developers to tackle annotation-scarce tasks, deploy high-performance models ...

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 ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

tumor cases and BI-RADS annotations in categories 2, 3, 4, and 5. In addition, the dataset also contains ground truth delineations that divide the BUS images into tumoral and normal regions. If you ...

Brain tumor detection and segmentation are critical tasks in medical imaging analysis for diagnosis and treatment planning. In recent years, computer vision techniques, particularly those implemented ...