18 citations · 62 across the 13 of their papers we have counts for
7 papers · 1 filter
High-resolution 3T to 7T MRI Synthesis with a Hybrid CNN-Transformer Model
Zach Eidex, Jing Wang, Mojtaba Safari +6
7 Tesla (7T) apparent diffusion coefficient (ADC) maps derived from diffusion-weighted imaging (DWI) demonstrate improved image quality and spatial resolution over 3 Tesla (3T) ADC…
Full-dose Whole-body PET Synthesis from Low-dose PET Using High-efficiency Denoising Diffusion Probabilistic Model: PET Consistency Model
Shaoyan Pan, Elham Abouei, Junbo Peng +8
Objective: Positron Emission Tomography (PET) has been a commonly used imaging modality in broad clinical applications. One of the most important tradeoffs in PET imaging is betwee…
Hippocampus Substructure Segmentation Using Morphological Vision Transformer Learning
Yang Lei, Yifu Ding, Richard L. J. Qiu +6
Background: The hippocampus plays a crucial role in memory and cognition. Because of the associated toxicity from whole brain radiotherapy, more advanced treatment planning techniq…
Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model
Shaoyan Pan, Elham Abouei, Jacob Wynne +10
Magnetic resonance imaging (MRI)-based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error-prone…
Cross-Shaped Windows Transformer with Self-supervised Pretraining for Clinically Significant Prostate Cancer Detection in Bi-parametric MRI
Yuheng Li, Jacob Wynne, Jing Wang +8
Biparametric magnetic resonance imaging (bpMRI) has demonstrated promising results in prostate cancer (PCa) detection using convolutional neural networks (CNNs). Recently, transfor…
Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis
Shaoyan Pan, Chih-Wei Chang, Junbo Peng +7
This study aims to develop a novel Cycle-guided Denoising Diffusion Probability Model (CG-DDPM) for cross-modality MRI synthesis. The CG-DDPM deploys two DDPMs that condition each…
Denoising Magnetic Resonance Spectroscopy (MRS) Data Using Stacked Autoencoder for Improving Signal-to-Noise Ratio and Speed of MRS
Jing Wang, Bing Ji, Yang Lei +3
Background: Magnetic resonance spectroscopy (MRS) enables non-invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal-to-noise ratio (SNR) w…