10 papers
U-TTT: Towards Generalizable PET Image Denoising via Test-Time Training
Zhiwen Yang, Jiayin Li, Hao Lu +3
Existing deep learning models for Positron Emission Tomography (PET) image denoising often suffer from severe performance degradation under distribution shifts, fundamentally restr…
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…
MedVol-R1: Reward-Driven Evidence Grounding for Volumetric Reasoning Segmentation
Zichun Wang, Hairong Shi, Bingzheng Wei +2
Volumetric Reasoning Segmentation (VRS) aims to segment a target region in a 3D medical scan from a free-form clinical query, where the referent is often implicit and requires both…
CTIS-QA: Clinical Template-Informed Slide-level Question Answering for Pathology
Hao Lu, Ziniu Qian, Yifu Li +3
In this paper, we introduce a clinical diagnosis template-based pipeline to systematically collect and structure pathological information. In collaboration with pathologists and gu…
TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration
Zhiwen Yang, Jiaju Zhang, Yang Yi +3
Medical image restoration (MedIR) aims to recover high-quality medical images from their low-quality counterparts. Recent advancements in MedIR have focused on All-in-One models ca…
All-in-One Medical Image Restoration with Latent Diffusion-Enhanced Vector-Quantized Codebook Prior
Haowei Chen, Zhiwen Yang, Haotian Hou +4
All-in-one medical image restoration (MedIR) aims to address multiple MedIR tasks using a unified model, concurrently recovering various high-quality (HQ) medical images (e.g., MRI…