Photoacoustic imaging (PAI) is a promising emerging imaging modality that enables
spatially resolved imaging of optical tissue properties up to several centimeters deep in …

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 …

Abstract Machine learning has been developed dramatically and witnessed a lot of
applications in various fields over the past few years. This boom originated in 2009, when a …

Conventional reconstruction algorithms (eg, delay-and-sum) used in photoacoustic imaging
(PAI) provide a fast solution while many artifacts remain, especially for limited-view with ill …

Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …

Recent advances in photoacoustic (PA) imaging have enabled detailed images of
microvascular structure and quantitative measurement of blood oxygenation or perfusion …

Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits
of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities …

Significance: Photoacoustic (PA) imaging can provide structural, functional, and molecular
information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal …

Medical image reconstruction methods based on deep learning have recently demonstrated
powerful performance in photoacoustic tomography (PAT) from limited-view and sparse …

Significance: Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to
the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image …