Abstract: Few-shot semantic segmentation (FSS) of 3D medical images requires finding a 2D slice from the labeled volume as support to ‘query’ slices of the unlabeled one. Accurately determining ...

This repository is the official PyTorch implementation of the ICCV 2025 (Highlight) paper: Images as Noisy Labels: Unleashing the Potential of the Diffusion Model for Open-Vocabulary Semantic ...

Frustrated by the medical system, some patients are turning to chatbots for help. At what cost? Credit...Pablo Delcan Supported by By Teddy Rosenbluth and Maggie Astor Wendy Goldberg thought her ...

Semantic segmentation of remote sensing images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high expense of manual annotation ...

1 School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China 2 School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, ...

Abstract: Semi-supervised learning has proven highly effective in tackling the challenge of limited labeled training data in medical image segmentation. In general, current approaches, which rely on ...

In recent years, semi-supervised methods have been rapidly developed for three-dimensional (3D) medical image analysis. However, previous semi-supervised methods for three-dimensional medical images ...