8 papers
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…
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…
LensPlus: A High Space-bandwidth Optical Imaging Technique
Neha Goswami, Mark A. Anastasio
The space-bandwidth product (SBP) imposes a fundamental limitation in achieving high-resolution and large field-of-view image acquisitions simultaneously. High-NA objectives provid…
Stochastic numerical head phantoms to enable virtual imaging studies of transcranial photoacoustic computed tomography
Hsuan-Kai Huang, Joseph Kuo, Seonyeong Park +3
Transcranial photoacoustic computed tomography (PACT) is an emerging neuroimaging modality, but skull-induced aberrations can result in severe image artifacts if not compensated fo…
Application of a Virtual Imaging Framework for Investigating a Deep Learning-Based Reconstruction Method for 3D Quantitative Photoacoustic Computed Tomography
Refik Mert Cam, Seonyeong Park, Umberto Villa +1
Quantitative photoacoustic computed tomography (qPACT) is a promising imaging modality for estimating physiological parameters such as blood oxygen saturation. However, developing…