1 citations · 2 across the 12 of their papers we have counts for
12 papers
MUX-USCT: A Noise-Robust Neural Network for Ultrasound Computed Tomography
Yuchen Yuan, Hanhan Wu, Jinyang Li +4
Deep neural networks (DNNs) have shown strong potential for ultrasound computed tomography (USCT) reconstruction in ideal noise-free environments, yet existing DNNs are vulnerable…
Improving Full Waveform Inversion in Large Model Era
Yinan Feng, Peng Jin, Yuzhe Guo +2
Full Waveform Inversion (FWI) is a highly nonlinear and ill-posed problem that aims to recover subsurface velocity maps from surface-recorded seismic waveforms data. Existing data-…
BrainPuzzle: Hybrid Physics and Data-Driven Reconstruction for Transcranial Ultrasound Tomography
Shengyu Chen, Shihang Feng, Yi Luo +2
Ultrasound brain imaging remains challenging due to the large difference in sound speed between the skull and brain tissues and the difficulty of coupling large probes to the skull…
OpenPros: A Large-Scale Dataset for Limited View Prostate Ultrasound Computed Tomography
Hanchen Wang, Yixuan Wu, Yinan Feng +11
Prostate cancer is one of the most prevalent and deadly cancers among men, motivating the development of accurate and accessible imaging technologies for early detection. Ultrasoun…
Learned Correction Methods for Ultrasound Computed Tomography Imaging Using Simplified Physics Models
Luke Lozenski, Hanchen Wang, Fu Li +4
Ultrasound computed tomography (USCT) is an emerging modality for breast imaging. Image reconstruction methods that incorporate accurate wave physics produce high resolution quanti…
On a Hidden Property in Computational Imaging
Yinan Feng, Yinpeng Chen, Yueh Lee +1
Computational imaging plays a vital role in various scientific and medical applications, such as Full Waveform Inversion (FWI), Computed Tomography (CT), and Electromagnetic (EM) i…
WaveDiffusion: Joint Latent Diffusion for Physically Consistent Seismic and Velocity Generation
Yinan Feng, Hanchen Wang, Yinpeng Chen +5
Full Waveform Inversion (FWI) is a critical technique in subsurface imaging, aiming to reconstruct high-resolution subsurface properties from surface measurements. Acoustic FWI inv…
Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging
Youzuo Lin, Shihang Feng, James Theiler +7
Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include…
PreMevE-MEO: Predicting Ultra-relativistic Electrons Using Observations from GPS Satellites
Yinan Feng, Yue Chen, Youzuo Lin
Ultra-relativistic electrons with energies greater than or equal to two megaelectron-volt (MeV) pose a major radiation threat to spaceborne electronics, and thus specifying those h…
A Physics-guided Generative AI Toolkit for Geophysical Monitoring
Junhuan Yang, Hanchen Wang, Yi Sheng +2
Full-waveform inversion (FWI) plays a vital role in geoscience to explore the subsurface. It utilizes the seismic wave to image the subsurface velocity map. As the machine learning…
DeFault: Deep-learning-based Fault Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site
Hanchen Wang, Yinpeng Chen, Tariq Alkhalifah +3
The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledg…
Exploring Invariance in Images through One-way Wave Equations
Yinpeng Chen, Dongdong Chen, Xiyang Dai +5
In this paper, we empirically reveal an invariance over images-images share a set of one-way wave equations with latent speeds. Each image is uniquely associated with a solution to…