37 citations · 117 across the 16 of their papers we have counts for
16 papers
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…
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…
Overview of Physics-Informed Machine Learning Inversion of Geophysical Data
Gerard T. Schuster, Shihang Feng
We review four types of algorithms for physics-informed machine learning (PIML) inversion of geophysical data. The unifying equation is given by the joint objective function : \…
An Empirical Study of Large-Scale Data-Driven Full Waveform Inversion
Peng Jin, Yinan Feng, Shihang Feng +5
This paper investigates the impact of big data on deep learning models to help solve the full waveform inversion (FWI) problem. While it is well known that big data can boost the p…
HOSSnet: an Efficient Physics-Guided Neural Network for Simulating Crack Propagation
Shengyu Chen, Shihang Feng, Yao Huang +4
Hybrid Optimization Software Suite (HOSS), which is a combined finite-discrete element method (FDEM), is one of the advanced approaches to simulating high-fidelity fracture and fra…
: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties
Shihang Feng, Hanchen Wang, Chengyuan Deng +6
Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO sequestration and energy exploration (e.g.,…
Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness
Min Zhu, Shihang Feng, Youzuo Lin +1
Full waveform inversion (FWI) infers the subsurface structure information from seismic waveform data by solving a non-convex optimization problem. Data-driven FWI has been increasi…
Auto-Linear Phenomenon in Subsurface Imaging
Yinan Feng, Yinpeng Chen, Peng Jin +3
Subsurface imaging involves solving full waveform inversion (FWI) to predict geophysical properties from measurements. This problem can be reframed as an image-to-image translation…
Solving Seismic Wave Equations on Variable Velocity Models with Fourier Neural Operator
Bian Li, Hanchen Wang, Shihang Feng +2
In the study of subsurface seismic imaging, solving the acoustic wave equation is a pivotal component in existing models. The advancement of deep learning enables solving partial d…
An Intriguing Property of Geophysics Inversion
Yinan Feng, Yinpeng Chen, Shihang Feng +3
Inversion techniques are widely used to reconstruct subsurface physical properties (e.g., velocity, conductivity) from surface-based geophysical measurements (e.g., seismic, electr…
Extremely Weak Supervision Inversion of Multi-physical Properties
Shihang Feng, Peng Jin, Xitong Zhang +4
Multi-physical inversion plays a critical role in geophysics. It has been widely used to infer various physical properties~(such as velocity and conductivity). Among those inversio…
OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion
Chengyuan Deng, Shihang Feng, Hanchen Wang +6
Full waveform inversion (FWI) is widely used in geophysics to reconstruct high-resolution velocity maps from seismic data. The recent success of data-driven FWI methods results in…
Connect the Dots: In Situ 4D Seismic Monitoring of CO2 Storage with Spatio-temporal CNNs
Shihang Feng, Xitong Zhang, Brendt Wohlberg +2
4D seismic imaging has been widely used in CO sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-t…
InversionNet3D: Efficient and Scalable Learning for 3D Full Waveform Inversion
Qili Zeng, Shihang Feng, Brendt Wohlberg +1
Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has s…
Multiscale Data-driven Seismic Full-waveform Inversion with Field Data Study
Shihang Feng, Youzuo Lin, Brendt Wohlberg
Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration g…