157 citations · 246 across the 15 of their papers we have counts for
7 papers · 1 filter
GraphMAR: Geometry-Aware Graph Learning Framework for Spatially Adaptive CT Metal Artifact Reduction
Zilong Li, Chenglong Ma, Yiming Lei +7
Computed tomography (CT) metal artifact reduction (MAR) aims to reduce the severe streaking artifacts induced by metallic implants and other high-density objects. Effective MAR gen…
PHASOR: Anatomy- and Phase-Consistent Volumetric Diffusion for CT Virtual Contrast Enhancement
Zilong Li, Dongyang Li, Chenglong Ma +6
Contrast-enhanced computed tomography (CECT) is pivotal for highlighting tissue perfusion and vascularity, yet its clinical ubiquity is impeded by the invasive nature of contrast a…
FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising
Zhihao Chen, Qi Gao, Zilong Li +4
Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despite significant advancements drive…
Prompt-In-Prompt Learning for Universal Image Restoration
Zilong Li, Yiming Lei, Chenglong Ma +2
Image restoration, which aims to retrieve and enhance degraded images, is fundamental across a wide range of applications. While conventional deep learning approaches have notably…
LICO: Explainable Models with Language-Image Consistency
Yiming Lei, Zilong Li, Yangyang Li +2
Interpreting the decisions of deep learning models has been actively studied since the explosion of deep neural networks. One of the most convincing interpretation approaches is sa…
CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction
Yiming Lei, Zilong Li, Yan Shen +2
Lung nodule malignancy prediction has been enhanced by advanced deep-learning techniques and effective tricks. Nevertheless, current methods are mainly trained with cross-entropy l…
CORE: Learning Consistent Ordinal REpresentations for Image Ordinal Estimation
Yiming Lei, Zilong Li, Yangyang Li +2
The goal of image ordinal estimation is to estimate the ordinal label of a given image with a convolutional neural network. Existing methods are mainly based on ordinal regression…