Deep learning in photoacoustic tomography: current approaches and future directions

A Hauptmann, B Cox - Journal of Biomedical Optics, 2020 - spiedigitallibrary.org
Biomedical photoacoustic tomography, which can provide high-resolution 3D soft tissue
images based on optical absorption, has advanced to the stage at which translation from the …

Least-squares reverse time migration via deep learning-based updating operators

K Torres, M Sacchi - Geophysics, 2022 - library.seg.org
Two common issues of least-squares reverse time migration (LSRTM) consist of the many
iterations required to produce substantial subsurface imaging improvements and the …

Multi-scale learned iterative reconstruction

A Hauptmann, J Adler, S Arridge… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Model-based learned iterative reconstruction methods have recently been shown to
outperform classical reconstruction algorithms. Applicability of these methods to large scale …

On Learning the Invisible in Photoacoustic Tomography with Flat Directionally Sensitive Detector

B Pan, MM Betcke - SIAM Journal on Imaging Sciences, 2023 - SIAM
In photoacoustic tomography (PAT) with a flat sensor, we routinely encounter two types of
limited data. The first is due to using a finite sensor and is especially perceptible if the region …

深度学习在有限视角稀疏采样光声图像重建中的应用.

孙正, 候英飒 - Journal of Data Acquisition & Processing/Shu …, 2022 - search.ebscohost.com
光声成像(Photoacoustic imaging, PAI) 是一种多物理场耦合的新型功能成像技术,
高质量图像重建是提高成像精度的关键. 当探测器采集的光声信号数据不完备时 …

Methods for Photoacoustic Image Reconstruction Exploiting Properties of Curvelet Frame

B Pan - 2022 - discovery.ucl.ac.uk
Curvelet frame is of special significance for photoacoustic tomography (PAT) due to its
sparsifying and microlocalisation properties. In this PhD project, we explore the methods for …