6 accepted papers
Understanding how transcriptomic programs shape tissue morphology remains a central challenge in computational pathology. Gene-to-WSI tile synthesis offers a principled generative framework to translate molecular profiles into histological images. However, most existing methods compress RNA-Seq into
Automated radiology report generation offers an effective solution to alleviate radiologists' workload. However, most existing methods focus primarily on single or fixed-view images to model current disease conditions, which limits diagnostic accuracy and overlooks disease progression. Although some…
The rapid advancements in Vision Language Models (VLMs) have prompted the development of multi-modal medical assistant systems. Despite this progress, current models still have inherent probabilistic uncertainties, often producing erroneous or unverified responses--an issue with serious implications…
Recent approaches to vision-language tasks are built on the remarkable capabilities of large vision-language models (VLMs). These models excel in zero-shot and few-shot learning, enabling them to learn new tasks without parameter updates. However, their primary challenge lies in their design, which…
"Detecting objects seamlessly blended into their surroundings represents a complex task for both human cognitive capabilities and advanced artificial intelligence algorithms. Currently, the majority of methodologies for detecting camouflaged objects mainly focus on utilizing discriminative models wi…
In this paper, we study the problem of salient object detection for RGB-D images by using both color and depth information. A major technical challenge for detecting salient objects in RGB-D images is to fully leverage the two complementary data sources. The existing works either simply distill prio…