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20242026
most citedNoise Level Adaptive Diffusion Model for Robust Reconstruction of Accelerated MRI

4 citations · 5 across the 6 of their papers we have counts for

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eess.IV2025

A Two-Stage Strategy for Mitosis Detection Using Improved YOLO11x Proposals and ConvNeXt Classification

Jie Xiao, Mengye Lyu, Shaojun Liu

MIDOG 2025 Track 1 requires mitosis detection in whole-slideimages (WSIs) containing non-tumor, inflamed, and necrotic re-gions. Due to the complicated and heterogeneous context, a…

eess.IV2025

MRI Image Generation Based on Text Prompts

Xinxian Fan, Mengye Lyu

This study explores the use of text-prompted MRI image generation with the Stable Diffusion (SD) model to address challenges in acquiring real MRI datasets, such as high costs, lim…

eess.IV2024

LDPM: Towards undersampled MRI reconstruction with MR-VAE and Latent Diffusion Prior

Xingjian Tang, Jingwei Guan, Linge Li +4

Diffusion models, as powerful generative models, have found a wide range of applications and shown great potential in solving image reconstruction problems. Some works attempted to…

eess.IV2024★ 1 cited

Robust Simultaneous Multislice MRI Reconstruction Using Slice-Wise Learned Generative Diffusion Priors

Shoujin Huang, Guanxiong Luo, Yunlin Zhao +8

Simultaneous multislice (SMS) imaging is a powerful technique for accelerating magnetic resonance imaging (MRI) acquisitions. However, SMS reconstruction remains challenging due to…

eess.IV2024★ 4 cited

Noise Level Adaptive Diffusion Model for Robust Reconstruction of Accelerated MRI

Shoujin Huang, Guanxiong Luo, Xi Wang +6

In general, diffusion model-based MRI reconstruction methods incrementally remove artificially added noise while imposing data consistency to reconstruct the underlying images. How…