46 citations · 129 across the 16 of their papers we have counts for
16 papers
A 3D-Printed Table for Hybrid X-ray CT and Optical Imaging of a Live Mouse
Wenxuan Xue, Yuxuan Liang, Mengzhou Li +3
Multimodal imaging has shown great potential in cancer research by concurrently providing anatomical, functional, and molecular information in live, intact animals. During preclini…
3D Photon Counting CT Image Super-Resolution Using Conditional Diffusion Model
Chuang Niu, Christopher Wiedeman, Mengzhou Li +2
This study aims to improve photon counting CT (PCCT) image resolution using denoising diffusion probabilistic models (DDPM). Although DDPMs have shown superior performance when app…
Data-driven imaging geometric recovery of ultrahigh resolution robotic micro-CT for in-vivo and other applications
Mengzhou Li, Guibin Zan, Wenbin Yun +3
We introduce an ultrahigh-resolution (50μm\) robotic micro-CT design for localized imaging of carotid plaques using robotic arms, cutting-edge detector, and machine learning techno…
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…
Photon-counting CT using a Conditional Diffusion Model for Super-resolution and Texture-preservation
Christopher Wiedeman, Chuang Niu, Mengzhou Li +3
Ultra-high resolution images are desirable in photon counting CT (PCCT), but resolution is physically limited by interactions such as charge sharing. Deep learning is a possible me…
Coronary Atherosclerotic Plaque Characterization with Photon-counting CT: a Simulation-based Feasibility Study
Mengzhou Li, Mingye Wu, Jed Pack +5
Recent development of photon-counting CT (PCCT) brings great opportunities for plaque characterization with much-improved spatial resolution and spectral imaging capability. While…
Systematic Review on Learning-based Spectral CT
Alexandre Bousse, Venkata Sai Sundar Kandarpa, Simon Rit +5
Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main for…
Motion Correction via Locally Linear Embedding for Helical Photon-counting CT
Mengzhou Li, Chiara Lowe, Anthony Butler +2
X-ray photon-counting detector (PCD) offers low noise, high resolution, and spectral characterization, representing a next generation of CT and enabling new biomedical applications…
Top-level Design and Simulated Performance of the First Portable CT-MR scanner
Yuting Peng, Mengzhou Li, Jace Grandinetti +2
Multi-modality imaging hardware can be integrated in a single gantry to collect diverse datasets for complementary information and spatiotemporal correlation, with excellent exampl…
On Expressivity and Trainability of Quadratic Networks
Feng-Lei Fan, Mengzhou Li, Fei Wang +2
Inspired by the diversity of biological neurons, quadratic artificial neurons can play an important role in deep learning models. The type of quadratic neurons of our interest repl…
Clinical Micro-CT Empowered by Interior Tomography, Robotic Scanning, and Deep Learning
Mengzhou Li, Zheng Fang, Wenxiang Cong +6
While micro-CT systems are instrumental in preclinical research, clinical micro-CT imaging has long been desired with cochlear implantation as a primary example. The structural det…
Suppression of Correlated Noise with Similarity-based Unsupervised Deep Learning
Chuang Niu, Mengzhou Li, Fenglei Fan +4
Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and photon-counting computed tomography (CT) denoising can optimize diagnostic performance at minimi…
Low-dimensional Manifold Constrained Disentanglement Network for Metal Artifact Reduction
Chuang Niu, Wenxiang Cong, Fenglei Fan +4
Deep neural network based methods have achieved promising results for CT metal artifact reduction (MAR), most of which use many synthesized paired images for training. As synthesiz…
X-ray Photon-Counting Data Correction through Deep Learning
Mengzhou Li, David S. Rundle, Ge Wang
X-ray photon-counting detectors (PCDs) are drawing an increasing attention in recent years due to their low noise and energy discrimination capabilities. The energy/spectral dimens…
On Interpretability of Artificial Neural Networks: A Survey
Fenglei Fan, Jinjun Xiong, Mengzhou Li +1
Deep learning as represented by the artificial deep neural networks (DNNs) has achieved great success in many important areas that deal with text, images, videos, graphs, and so on…
Soft Autoencoder and Its Wavelet Adaptation Interpretation
Fenglei Fan, Mengzhou Li, Yueyang Teng +1
Recently, deep learning becomes the main focus of machine learning research and has greatly impacted many important fields. However, deep learning is criticized for lack of interpr…