Background: 3D medical image segmentation is a cornerstone for quantitative analysis and clinical decision-making in various modalities. However, acquiring high-quality voxel-level annotations is both ...

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 ...

1 School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China 2 College of Information Science and Technology, Nanjing Forestry University, Nanjing, China ...

As shown below, the inferred masks predicted by our segmentation model trained on the PNG dataset appear similar to the ground truth masks, but they lack precision in certain areas. As shown above, ...

ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...

Our (HDR) Our model trained on our HDR dataset with unpaired data Our (SL) Our model trained on MIT-Adobe 5K dataset with paired data (supervised learning) Our (UL) Our model trained on MIT-Adobe 5K ...

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...

Abstract: Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to ...

Elon Musk’s AI company has officially rolled out Grok Imagine, xAI’s image and video generator, to all SuperGrok and Premium+ X subscribers on its iOS app. And true to form for Musk, who positions ...

Abstract: Semi-supervised learning offers an appealing solution for remote sensing (RS) image segmentation to relieve the burden of labor-intensive pixel-level labeling. However, RS images pose unique ...