27 citations · 33 across the 6 of their papers we have counts for
7 papers
Distortion-Free High-Resolution PROPELLER-DWI: Technical Advances and Initial Demonstration for the Prostate
Jingjia Chen, Kun Zhou, Haoyang Pei +7
Purpose: To develop and evaluate an integrated acquisition and reconstruction framework for distortion-free, high-resolution prostate diffusion-weighted imaging (DWI). Methods: PRO…
Self-Supervised Joint Reconstruction and Denoising of T2-Weighted PROPELLER MRI of the Lungs at 0.55T
Jingjia Chen, Haoyang Pei, Christoph Maier +6
Purpose: This study aims to improve 0.55T T2-weighted PROPELLER lung MRI through a self-supervised joint reconstruction and denoising model. Methods: T2-weighted 0.55T lung MRI dat…
Hybrid Learning: A Novel Combination of Self-Supervised and Supervised Learning for Joint MRI Reconstruction and Denoising in Low-Field MRI
Haoyang Pei, Nikola Janjuvsevic, Renqing Luo +6
Deep learning has demonstrated strong potential for MRI reconstruction. However, conventional supervised learning requires high-quality, high-SNR references for network training, w…
DeepEMC-T2 Mapping: Deep Learning-Enabled T2 Mapping Based on Echo Modulation Curve Modeling
Haoyang Pei, Timothy M. Shepherd, Yao Wang +4
Purpose: Echo modulation curve (EMC) modeling can provide accurate and reproducible quantification of T2 relaxation times. The standard EMC-T2 mapping framework, however, requires…
Self-Supervised Learning based Depth Estimation from Monocular Images
Mayank Poddar, Akash Mishra, Mohit Kewlani +1
Depth Estimation has wide reaching applications in the field of Computer vision such as target tracking, augmented reality, and self-driving cars. The goal of Monocular Depth Estim…
Understanding the Impact of Image Quality and Distance of Objects to Object Detection Performance
Yu Hao, Haoyang Pei, Yixuan Lyu +4
Deep learning has made great strides for object detection in images. The detection accuracy and computational cost of object detection depend on the spatial resolution of an image,…
Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to "See" More, Farther and Faster
Zhongzheng Yuan, Tommy Azzino, Yu Hao +12
Advanced wearable devices are increasingly incorporating high-resolution multi-camera systems. As state-of-the-art neural networks for processing the resulting image data are compu…