31 citations · 46 across the 6 of their papers we have counts for
5 papers · 1 filter
Imaging foundation model for universal enhancement of non-ideal measurement CT
Rongjun Ge, Yuxin Liu, Zhan Wu +7
Non-ideal measurement computed tomography (NICT) employs suboptimal imaging protocols to expand CT applications. However, the resulting trade-offs degrade image quality, limiting c…
Multi-Conditioned Denoising Diffusion Probabilistic Model (mDDPM) for Medical Image Synthesis
Arjun Krishna, Ge Wang, Klaus Mueller
Medical imaging applications are highly specialized in terms of human anatomy, pathology, and imaging domains. Therefore, annotated training datasets for training deep learning app…
CT-based Anomaly Detection of Liver Tumors Using Generative Diffusion Prior
Yongyi Shi, Chuang Niu, Amber L. Simpson +3
CT is a main modality for imaging liver diseases, valuable in detecting and localizing liver tumors. Traditional anomaly detection methods analyze reconstructed images to identify…
Deep Few-view High-resolution Photon-counting CT at Halved Dose for Extremity Imaging
Mengzhou Li, Chuang Niu, Ge Wang +10
X-ray photon-counting computed tomography (PCCT) for extremity allows multi-energy high-resolution (HR) imaging but its radiation dose can be further improved. Despite the great po…
Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies
Jiahao Huang, Yinzhe Wu, Fanwen Wang +17
Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric…