22 citations · 63 across the 15 of their papers we have counts for
9 papers · 1 filter
Deep-learning-enabled Brain Hemodynamic Mapping Using Resting-state fMRI
Xirui Hou, Pengfei Guo, Puyang Wang +18
Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging met…
Towards performant and reliable undersampled MR reconstruction via diffusion model sampling
Cheng Peng, Pengfei Guo, S. Kevin Zhou +2
Magnetic Resonance (MR) image reconstruction from under-sampled acquisition promises faster scanning time. To this end, current State-of-The-Art (SoTA) approaches leverage deep neu…
On-the-Fly Test-time Adaptation for Medical Image Segmentation
Jeya Maria Jose Valanarasu, Pengfei Guo, Vibashan VS +1
One major problem in deep learning-based solutions for medical imaging is the drop in performance when a model is tested on a data distribution different from the one that it is tr…
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation
Pengfei Guo, Dong Yang, Ali Hatamizadeh +14
Federated learning (FL) is a distributed machine learning technique that enables collaborative model training while avoiding explicit data sharing. The inherent privacy-preserving…
ReconFormer: Accelerated MRI Reconstruction Using Recurrent Transformer
Pengfei Guo, Yiqun Mei, Jinyuan Zhou +2
Accelerating magnetic resonance image (MRI) reconstruction process is a challenging ill-posed inverse problem due to the excessive under-sampling operation in k-space. In this pape…
Over-and-Under Complete Convolutional RNN for MRI Reconstruction
Pengfei Guo, Jeya Maria Jose Valanarasu, Puyang Wang +3
Reconstructing magnetic resonance (MR) images from undersampled data is a challenging problem due to various artifacts introduced by the under-sampling operation. Recent deep learn…
Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
Pengfei Guo, Puyang Wang, Jinyuan Zhou +2
Fast and accurate reconstruction of magnetic resonance (MR) images from under-sampled data is important in many clinical applications. In recent years, deep learning-based methods…
Confidence-guided Lesion Mask-based Simultaneous Synthesis of Anatomic and Molecular MR Images in Patients with Post-treatment Malignant Gliomas
Pengfei Guo, Puyang Wang, Rajeev Yasarla +3
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas in neuro-oncology, especially with the help of standard a…
Customized OCT images compression scheme with deep neural network
Pengfei Guo, Dawei Li, Xingde Li
We customize an end-to-end image compression framework for retina OCT images based on deep convolutional neural networks (CNNs). The customized compression scheme consists of three…