21 citations · 37 across the 17 of their papers we have counts for
14 papers · 1 filter
UniH: Unifying Hierarchical Homogeneity and Heterogeneity for All-in-One Medical Image Restoration
Zhiwen Yang, Jiayin Li, Chengyu Liu +3
All-in-One medical image restoration (MedIR) aims to address diverse tasks across modalities and degradation types using a single universal model. Existing methods typically priori…
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…
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…
Visual Textualization for Image Prompted Object Detection
Yongjian Wu, Yang Zhou, Jiya Saiyin +2
We propose VisTex-OVLM, a novel image prompted object detection method that introduces visual textualization -- a process that projects a few visual exemplars into the text feature…
FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation
Huihan Wang, Zhiwen Yang, Hui Zhang +3
Synthesizing high-quality dynamic medical videos remains a significant challenge due to the need for modeling both spatial consistency and temporal dynamics. Existing Transformer-b…
AttriPrompter: Auto-Prompting with Attribute Semantics for Zero-shot Nuclei Detection via Visual-Language Pre-trained Models
Yongjian Wu, Yang Zhou, Jiya Saiyin +4
Large-scale visual-language pre-trained models (VLPMs) have demonstrated exceptional performance in downstream object detection through text prompts for natural scenes. However, th…
SDPT: Synchronous Dual Prompt Tuning for Fusion-based Visual-Language Pre-trained Models
Yang Zhou, Yongjian Wu, Jiya Saiyin +4
Prompt tuning methods have achieved remarkable success in parameter-efficient fine-tuning on large pre-trained models. However, their application to dual-modal fusion-based visual-…
All-In-One Medical Image Restoration via Task-Adaptive Routing
Zhiwen Yang, Haowei Chen, Ziniu Qian +5
Although single-task medical image restoration (MedIR) has witnessed remarkable success, the limited generalizability of these methods poses a substantial obstacle to wider applica…
Zero-shot Nuclei Detection via Visual-Language Pre-trained Models
Yongjian Wu, Yang Zhou, Jiya Saiyin +5
Large-scale visual-language pre-trained models (VLPM) have proven their excellent performance in downstream object detection for natural scenes. However, zero-shot nuclei detection…
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation
Yang Zhou, Yongjian Wu, Zihua Wang +5
Nuclei instance segmentation on histopathology images is of great clinical value for disease analysis. Generally, fully-supervised algorithms for this task require pixel-wise manua…
Transformer based multiple instance learning for weakly supervised histopathology image segmentation
Ziniu Qian, Kailu Li, Maode Lai +4
Hispathological image segmentation algorithms play a critical role in computer aided diagnosis technology. The development of weakly supervised segmentation algorithm alleviates th…