human teeth imaging with various photoacoustic imaging systems.

Dental caries cause pain and if not diagnosed, it may lead to the loss of teeth in extreme cases. Dental X-ray imaging is the gold standard for caries detection; however, it cannot detect hidden caries. In addition, the ionizing nature of X-ray radiation is another concern.

Ultrasound-guided needle tracking with deep learning: A novel approach with photoacoustic ground truth.

Accurate needle guidance is crucial for safe and effective clinical diagnosis and treatment procedures. Conventional ultrasound (US)-guided needle insertion often encounters challenges in consistency and precisely visualizing the needle, necessitating the development of reliable methods to track the needle. As a powerful tool in image processing, deep learning has shown promise for enhancing needle visibility in US images, although its dependence on manual annotation or simulated data as ground truth can lead to potential bias or difficulties in generalizing to real US images.

Special Section Guest Editorial: Seeing Inside Tissue with Optical Molecular Probes.

The editorial introduces the Special Section on Seeing Inside Tissue with Optical Molecular Probes.

Physics-guided neural network for tissue optical properties estimation.

Finding the optical properties of tissue is essential for various biomedical diagnostic/therapeutic applications such as monitoring of blood oxygenation, tissue metabolism, skin imaging, photodynamic therapy, low-level laser therapy, and photo-thermal therapy. Hence, the research for more accurate and versatile optical properties estimation techniques has always been a primary interest of researchers, especially in the field of bioimaging and bio-optics. In the past, most of the prediction methods were based on physics-based models such as the pronounced diffusion approximation method.

Android mobile-platform-based image reconstruction for photoacoustic tomography.

Significance: In photoacoustic tomography (PAT), numerous reconstruction algorithms have been utilized to recover initial pressure rise distribution from the acquired pressure waves. In practice, most of these reconstructions are carried out on a desktop/workstation and the mobile-based reconstructions are far-flung. In recent years, mobile phones are becoming so ubiquitous, and most of them encompass a higher computing ability.

Adaptive enhancement of acoustic resolution photoacoustic microscopy imaging deep CNN prior.

Acoustic resolution photoacoustic microscopy (AR-PAM) is a promising medical imaging modality that can be employed for deep bio-tissue imaging. However, its relatively low imaging resolution has greatly hindered its wide applications. Previous model-based or learning-based PAM enhancement algorithms either require design of complex handcrafted prior to achieve good performance or lack the interpretability and flexibility that can adapt to different degradation models.

High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning.

Significance: In circular scanning photoacoustic tomography (PAT), it takes several minutes to generate an image of acceptable quality, especially with a single-element ultrasound transducer (UST). The imaging speed can be enhanced by faster scanning (with high repetition rate light sources) and using multiple-USTs. However, artifacts arising from the sparse signal acquisition and low signal-to-noise ratio at higher scanning speeds limit the imaging speed.

Looking deep inside tissue with photoacoustic molecular probes: a review.

Significance: Deep tissue noninvasive high-resolution imaging with light is challenging due to the high degree of light absorption and scattering in biological tissue. Photoacoustic imaging (PAI) can overcome some of the challenges of pure optical or ultrasound imaging to provide high-resolution deep tissue imaging. However, label-free PAI signals from light absorbing chromophores within the tissue are nonspecific.

Deep and Domain Transfer Learning Aided Photoacoustic Microscopy: Acoustic Resolution to Optical Resolution.

Acoustic resolution photoacoustic micros- copy (AR-PAM) can achieve deeper imaging depth in biological tissue, with the sacrifice of imaging resolution compared with optical resolution photoacoustic microscopy (OR-PAM). Here we aim to enhance the AR-PAM image quality towards OR-PAM image, which specifically includes the enhancement of imaging resolution, restoration of micro-vasculatures, and reduction of artifacts. To address this issue, a network (MultiResU-Net) is first trained as generative model with simulated AR-OR image pairs, which are synthesized with physical transducer model.

Multi-angle data acquisition to compensate transducer finite size in photoacoustic tomography.

In photoacoustic tomography (PAT) systems, the tangential resolution decreases due to the finite size of the transducer as the off-center distance increases. To address this problem, we propose a multi-angle detection approach in which the transducer used for data acquisition rotates around its center (with specific angles) as well as around the scanning center. The angles are calculated based on the central frequency and diameter of the transducer and the radius of the region-of-interest (ROI).

Photoacoustic imaging aided with deep learning: a review.

Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities, its translation into clinics is still hindered by various limitations. In recent years, deeplearning (DL), a new paradigm of machine learning, is gaining a lot of attention due to its ability to improve medical images.

Accuracy of peak-power compensation in fiber-guided and free-space acoustic-resolution photoacoustic microscopy.

Acoustic resolution photoacoustic microscopy (AR-PAM) has gained much attention in the past two decades due to its high contrast, scalable resolution, and relatively higher imaging depth. Multimode optical fibers (MMF) are extensively used to transfer light to AR-PAM imaging scan-head from the laser source. Typically, peak-power-compensation (PPC) is used to reduce the effect of pulse-to-pulse peak-power variation in generated photoacoustic (PA) signals.

Hybrid Carbon Dot Assembly as a Reactive Oxygen Species Nanogenerator for Ultrasound-Assisted Tumor Ablation.

The efficacy of reactive oxygen species (ROS)-based therapy is substantially constrained by the limited ROS generation, stern activation conditions, and lack of a straightforward reaction paradigm. Carbon dots (CDs) have been highly sought after for therapeutic applications for their biocompatibility and intrinsic fluorescence imaging capabilities, making them suitable for ROS generation. Herein, we synthesized a CD-based ultrasmall hybrid nanostructure possessing active sites of Mo, Cu, and IR-780 dye.

Deep-learning-based multi-transducer photoacoustic tomography imaging without radius calibration.

Pulsed laser diodes are used in photoacoustic tomography (PAT) as excitation sources because of their low cost, compact size, and high pulse repetition rate. In combination with multiple single-element ultrasound transducers (SUTs) the imaging speed of PAT can be improved. However, during PAT image reconstruction, the exact radius of each SUT is required for accurate reconstruction.

Binary photoacoustic tomography for improved vasculature imaging.

Significance: The proposed binary tomography approach was able to recover the vasculature structures accurately, which could potentially enable the utilization of binary tomography algorithm in scenarios such as therapy monitoring and hemorrhage detection in different organs.

Aim: Photoacoustic tomography (PAT) involves reconstruction of vascular networks having direct implications in cancer research, cardiovascular studies, and neuroimaging. Various methods have been proposed for recovering vascular networks in photoacoustic imaging; however, most methods are two-step (image reconstruction and image segmentation) in nature.

Nanotechnology Facilitated Cultured Neuronal Network and Its Applications.

The development of a biomimetic neuronal network from neural cells is a big challenge for researchers. Recent advances in nanotechnology, on the other hand, have enabled unprecedented tools and techniques for guiding and directing neural stem cell proliferation and differentiation in vitro to construct an in vivo-like neuronal network. Nanotechnology allows control over neural stem cells by means of scaffolds that guide neurons to reform synaptic networks in suitable directions in 3D architecture, surface modification/nanopatterning to decide cell fate and stimulate/record signals from neurons to find out the relationships between neuronal circuit connectivity and their pathophysiological functions.

Ultrasonic Implantation and Imaging of Sound-Sensitive Theranostic Agents for the Treatment of Arterial Inflammation.

For site-specific diseases such as atherosclerosis, it is desirable to noninvasively and locally deliver therapeutics for extended periods of time. High-intensity focused ultrasound (HIFU) provides targeted drug delivery, yet remains unable to sustain delivery beyond the HIFU treatment time. Furthermore, methods to validate HIFU-enhanced drug delivery remain limited.

Axial accuracy and signal enhancement in acoustic-resolution photoacoustic microscopy by laser jitter effect correction and pulse energy compensation.

In recent years, photoacoustic imaging has found vast applications in biomedical imaging. Photoacoustic imaging has high optical contrast and high ultrasound resolution allowing deep tissue non-invasive imaging beyond the optical diffusion limit. Q-switched lasers are extensively used in photoacoustic imaging due to the availability of high energy and short laser pulses, which are essential for high-resolution photoacoustic imaging.

Investigating the Acoustic Response and Contrast Enhancement of Drug-Loadable PLGA Microparticles with Various Shapes and Morphologies.

Polymer nanoparticles and microparticles have been used primarily for drug delivery. There is now growing interest in further developing polymer-based solid cavitation agents to also enhance ultrasound imaging. We previously reported on a facile method to produce hollow poly(lactic-co-glycolic acid) (PLGA) microparticles with different diameters and degrees of porosity.

Dimensionality reduced plug and play priors for improving photoacoustic tomographic imaging with limited noisy data.

The reconstruction methods for solving the ill-posed inverse problem of photoacoustic tomography with limited noisy data are iterative in nature to provide accurate solutions. These methods performance is highly affected by the noise level in the photoacoustic data. A singular value decomposition (SVD) based plug and play priors method for solving photoacoustic inverse problem was proposed in this work to provide robustness to noise in the data.

Sounding out the hidden data: A concise review of deep learning in photoacoustic imaging.

The rapidly evolving field of photoacoustic tomography utilizes endogenous chromophores to extract both functional and structural information from deep within tissues. It is this power to perform precise quantitative measurements with endogenous or exogenous contrastthat makes photoacoustic tomography highly promising for clinical translation in functional brain imaging, early cancer detection, real-time surgical guidance, and the visualization of dynamic drug responses. Considering photoacoustic tomography has benefited from numerous engineering innovations, it is of no surprise that many of photoacoustic tomography's current cutting-edge developments incorporate advances from the equally novel field of artificial intelligence.

Deep learning approach to improve tangential resolution in photoacoustic tomography.

In circular scan photoacoustic tomography (PAT), the axial resolution is spatially invariant and is limited by the bandwidth of the detector. However, the tangential resolution is spatially variant and is dependent on the aperture size of the detector. In particular, the tangential resolution improves with the decreasing aperture size.

Convolutional neural network for resolution enhancement and noise reduction in acoustic resolution photoacoustic microscopy.

In acoustic resolution photoacoustic microscopy (AR-PAM), a high numerical aperture focused ultrasound transducer (UST) is used for deep tissue high resolution photoacoustic imaging. There is a significant degradation of lateral resolution in the out-of-focus region. Improvement in out-of-focus resolution without degrading the image quality remains a challenge.

Another decade of photoacoustic imaging.

Photoacoustic imaging-a hybrid biomedical imaging modality finding its way to clinical practices. Although the photoacoustic phenomenon was known more than a century back, only in the last two decades it has been widely researched and used for biomedical imaging applications. In this review we focus on the development and progress of the technology in the last decade (2011-2020).