Abstract: Referring Image Segmentation (RIS) is a fundamental vision-language task that outputs object masks based on text descriptions. Many works have achieved considerable progress for RIS, ...
Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
IBISAgent is a novel agentic Multimodal Large Language Model (MLLM) framework designed to address the limitations of existing medical MLLMs in fine-grained pixel-level understanding. unlike previous ...
Scientists have created an AI tool that could help doctors identify diseases quickly and accurately using only a small number of medical images. Credit: Victoria Kotlyarchuk/iStock A new artificial ...
U-Net and its variants have been widely used in the field of image segmentation. In this paper, a lightweight multi-scale Ghost U-Net (MSGU-Net) network architecture is proposed. This can efficiently ...
Deep convolutional neural network (CNN) greatly promotes the automatic segmentation of medical images. However, due to the inherent properties of convolution operations, CNN usually cannot establish ...
Meta released a new artificial intelligence (AI) model this week that has the ability to identify specific objects in an image, as well as an entire dataset of image annotations that is said to be the ...
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