8 papers · 1 filter
UniPET: a universal network for high-quality PET image denoising across varied dose reduction factors
Zhiwen Yang, Yang Zhou, Haowei Chen +4
Most existing deep learning-based PET image denoising methods assume a fixed and known dose reduction factor (DRF) for low-dose PET images. However, these methods encounter signifi…
Unifying Multiple Foundation Models for Advanced Computational Pathology
Wenhui Lei, Yusheng Tan, Anqi Li +7
Foundation models have substantially advanced computational pathology by learning transferable visual representations from large histological datasets, yet their performance varies…
MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications
Yongrui Yu, Yannian Gu, Shaoting Zhang +1
Diffusion models have achieved significant success in both natural image and medical image domains, encompassing a wide range of applications. Previous investigations in medical im…
Towards Generalist Intelligence in Dentistry: Vision Foundation Models for Oral and Maxillofacial Radiology
Xinrui Huang, Fan Xiao, Dongming He +5
Oral and maxillofacial radiology plays a vital role in dental healthcare, but radiographic image interpretation is limited by a shortage of trained professionals. While AI approach…
MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression
Linjie Mu, Zhongzhen Huang, Shengqian Qin +3
Large vision-language models (LVLMs) have shown great promise in medical applications, particularly in visual question answering (MedVQA) and diagnosis from medical images. However…
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
Yankai Jiang, Wenhui Lei, Xiaofan Zhang +1
Recent advancements in medical vision-language pre-training models have driven significant progress in zero-shot disease recognition. However, transferring image-level knowledge to…