5 papers
A Learning-based Framework for Spatial Impulse Response Compensation in 3D Photoacoustic Computed Tomography
Kaiyi Yang, Seonyeong Park, Gangwon Jeong +4
Photoacoustic computed tomography (PACT) is a promising imaging modality that combines the advantages of optical contrast with ultrasound detection. Utilizing ultrasound transducer…
Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic Datasets
Panpan Chen, Seonyeong Park, Gangwon Jeong +3
Deep learning (DL)-based image reconstruction methods for photoacoustic computed tomography (PACT) have developed rapidly in recent years. However, most existing methods have not e…
A Virtual Imaging Framework for Three-Dimensional Quantitative Optoacoustic Tomography Using Stochastic Numerical Breast Phantoms
Seonyeong Park, Gangwon Jeong, Umberto Villa +1
Optoacoustic tomography (OAT) is a promising modality for breast cancer diagnosis because tumor angiogenesis and, potentially, hypoxia can be visualized using quantitative OAT (qOA…
Investigating the Use of Traveltime and Reflection Tomography for Deep Learning-Based Sound-Speed Estimation in Ultrasound Computed Tomography
Gangwon Jeong, Fu Li, Trevor M. Mitcham +3
Ultrasound computed tomography (USCT) quantifies acoustic tissue properties such as the speed-of-sound (SOS). Although full-waveform inversion (FWI) is an effective method for accu…
Revisiting the joint estimation of initial pressure and speed-of-sound distributions in photoacoustic computed tomography with consideration of canonical object constraints
Gangwon Jeong, Umberto Villa, Mark A. Anastasio
In photoacoustic computed tomography (PACT) the accurate estimation of the initial pressure (IP) distribution generally requires knowledge of the object's heterogeneous speed-of-so…