A Deep Reinforcement Learning Strategy for Surrounding Vehicles-Based Lane-Keeping Control.

As autonomous vehicles (AVs) are advancing to higher levels of autonomy and performance, the associated technologies are becoming increasingly diverse. Lane-keeping systems (LKS), corresponding to a key functionality of AVs, considerably enhance driver convenience. With drivers increasingly relying on autonomous driving technologies, the importance of safety features, such as fail-safe mechanisms in the event of sensor failures, has gained prominence. Therefore, this paper proposes a reinforcement learning (RL) control method for lane-keeping, which uses surrounding object information derived through LiDAR sensors instead of camera sensors for LKS. This approach uses surrounding vehicle and object information as observations for the RL framework to maintain the vehicle's current lane. The learning environment is established by integrating simulation tools, such as IPG CarMaker, which incorporates vehicle dynamics, and MATLAB Simulink for data analysis and RL model creation. To further validate the applicability of the LiDAR sensor data in real-world settings, Gaussian noise is introduced in the virtual simulation environment to mimic sensor noise in actual operational conditions.

Automated Laser-Fiber Coupling Module for Optical-Resolution Photoacoustic Microscopy.

Photoacoustic imaging has emerged as a promising biomedical imaging technique that enables visualization of the optical absorption characteristics of biological tissues in vivo. Among the different photoacoustic imaging system configurations, optical-resolution photoacoustic microscopy stands out by providing high spatial resolution using a tightly focused laser beam, which is typically transmitted through optical fibers. Achieving high-quality images depends significantly on optical fluence, which is directly proportional to the signal-to-noise ratio. Hence, optimizing the laser-fiber coupling is critical. Conventional coupling systems require manual adjustment of the optical path to direct the laser beam into the fiber, which is a repetitive and time-consuming process. In this study, we propose an automated laser-fiber coupling module that optimizes laser delivery and minimizes the need for manual intervention. By incorporating a motor-mounted mirror holder and proportional derivative control, we successfully achieved efficient and robust laser delivery. The performance of the proposed system was evaluated using a leaf-skeleton phantom in vitro and a human finger in vivo, resulting in high-quality photoacoustic images. This innovation has the potential to significantly enhance the quality and efficiency of optical-resolution photoacoustic microscopy.

TransNet: Transformer-Based Point Cloud Sampling Network.

As interest in point cloud processing has gradually increased in the industry, point cloud sampling techniques have been researched to improve deep learning networks. As many conventional models use point clouds directly, the consideration of computational complexity has become critical for practicality. One of the representative ways to decrease computations is downsampling, which also affects the performance in terms of precision. Existing classic sampling methods have adopted a standardized way regardless of the task-model property in learning. However, this limits the improvement of the point cloud sampling network's performance. That is, the performance of such task-agnostic methods is too low when the sampling ratio is high. Therefore, this paper proposes a novel downsampling model based on the transformer-based point cloud sampling network (TransNet) to efficiently perform downsampling tasks. The proposed TransNet utilizes self-attention and fully connected layers to extract meaningful features from input sequences and perform downsampling. By introducing attention techniques into downsampling, the proposed network can learn about the relationships between point clouds and generate a task-oriented sampling methodology. The proposed TransNet outperforms several state-of-the-art models in terms of accuracy. It has a particular advantage in generating points from sparse data when the sampling ratio is high. We expect that our approach can provide a promising solution for downsampling tasks in various point cloud applications.

Review on ultrasound-guided photoacoustic imaging for complementary analyses of biological systems in vivo.

Photoacoustic imaging has been developed as a new biomedical molecular imaging modality. Due to its similarity to conventional ultrasound imaging in terms of signal detection and image generation, dual-modal photoacoustic and ultrasound imaging has been applied to visualize physiological and morphological information in biological systems in vivo. By complementing each other, dual-modal photoacoustic and ultrasound imaging showed synergistic advances in photoacoustic imaging with the guidance of ultrasound images. In this review, we introduce our recent progresses in dual-modal photoacoustic and ultrasound imaging systems at various scales of study, from preclinical small animals to clinical humans. A summary of the works reveals various strategies for combining the structural information of ultrasound images with the molecular information of photoacoustic images.

Functional photoacoustic imaging: from nano- and micro- to macro-scale.

Functional photoacoustic imaging is a promising biological imaging technique that offers such unique benefits as scalable resolution and imaging depth, as well as the ability to provide functional information. At nanoscale, photoacoustic imaging has provided super-resolution images of the surface light absorption characteristics of materials and of single organelles in cells. At the microscopic and macroscopic scales. photoacoustic imaging techniques have precisely measured and quantified various physiological parameters, such as oxygen saturation, vessel morphology, blood flow, and the metabolic rate of oxygen, in both human and animal subjects. This comprehensive review provides an overview of functional photoacoustic imaging across multiple scales, from nano to macro, and highlights recent advances in technology developments and applications. Finally, the review surveys the future prospects of functional photoacoustic imaging in the biomedical field.

Recent Advances in Photoacoustic Agents for Theranostic Applications.

Photoacoustic agents are widely used in various theranostic applications. By evaluating the biodistribution obtained from photoacoustic images, the effectiveness of theranostic agents in terms of their delivery efficiency and treatment responses can be analyzed. Through this study, we evaluate and summarize the recent advances in photoacoustic-guided phototherapy, particularly in photothermal and photodynamic therapy. This overview can guide the future directions for theranostic development. Because of the recent applications of photoacoustic imaging in clinical trials, theranostic agents with photoacoustic monitoring have the potential to be translated into the clinical world.

Deep brain stimulation by blood-brain-barrier-crossing piezoelectric nanoparticles generating current and nitric oxide under focused ultrasound.

Deep brain stimulation via implanted electrodes can alleviate neuronal disorders. However, its applicability is constrained by side effects resulting from the insertion of electrodes into the brain. Here, we show that systemically administered piezoelectric nanoparticles producing nitric oxide and generating direct current under high-intensity focused ultrasound can be used to stimulate deep tissue in the brain. The release of nitric oxide temporarily disrupted tight junctions in the blood-brain barrier, allowing for the accumulation of the nanoparticles into brain parenchyma, and the piezoelectrically induced output current stimulated the release of dopamine by dopaminergic neuron-like cells. In a mouse model of Parkinson's disease, the ultrasound-responsive nanoparticles alleviated the symptoms of the disease without causing overt toxicity. The strategy may inspire the development of other minimally invasive therapies for neurodegenerative diseases.

Deep learning alignment of bidirectional raster scanning in high speed photoacoustic microscopy.

Simultaneous point-by-point raster scanning of optical and acoustic beams has been widely adapted to high-speed photoacoustic microscopy (PAM) using a water-immersible microelectromechanical system or galvanometer scanner. However, when using high-speed water-immersible scanners, the two consecutively acquired bidirectional PAM images are misaligned with each other because of unstable performance, which causes a non-uniform time interval between scanning points. Therefore, only one unidirectionally acquired image is typically used; consequently, the imaging speed is reduced by half. Here, we demonstrate a scanning framework based on a deep neural network (DNN) to correct misaligned PAM images acquired via bidirectional raster scanning. The proposed method doubles the imaging speed compared to that of conventional methods by aligning nonlinear mismatched cross-sectional B-scan photoacoustic images during bidirectional raster scanning. Our DNN-assisted raster scanning framework can further potentially be applied to other raster scanning-based biomedical imaging tools, such as optical coherence tomography, ultrasound microscopy, and confocal microscopy.

Contrast Agents for Photoacoustic Imaging: A Review Focusing on the Wavelength Range.

Photoacoustic imaging using endogenous chromophores as a contrast has been widely applied in biomedical studies owing to its functional imaging capability at the molecular level. Various exogenous contrast agents have also been investigated for use in contrast-enhanced imaging and functional analyses. This review focuses on contrast agents, particularly in the wavelength range, for use in photoacoustic imaging. The basic principles of photoacoustic imaging regarding light absorption and acoustic release are introduced, and the optical characteristics of tissues are summarized according to the wavelength region. Various types of contrast agents, including organic dyes, semiconducting polymeric nanoparticles, gold nanoparticles, and other inorganic nanoparticles, are explored in terms of their light absorption range in the near-infrared region. An overview of the contrast-enhancing capacity and other functional characteristics of each agent is provided to help researchers gain insights into the development of contrast agents in photoacoustic imaging.

Whole-Body Photoacoustic Imaging Techniques for Preclinical Small Animal Studies.

Photoacoustic imaging is a hybrid imaging technique that has received considerable attention in biomedical studies. In contrast to pure optical imaging techniques, photoacoustic imaging enables the visualization of optical absorption properties at deeper imaging depths. In preclinical small animal studies, photoacoustic imaging is widely used to visualize biodistribution at the molecular level. Monitoring the whole-body distribution of chromophores in small animals is a key method used in preclinical research, including drug-delivery monitoring, treatment assessment, contrast-enhanced tumor imaging, and gastrointestinal tracking. In this review, photoacoustic systems for the whole-body imaging of small animals are explored and summarized. The configurations of the systems vary with the scanning methods and geometries of the ultrasound transducers. The future direction of research is also discussed with regard to achieving a deeper imaging depth and faster imaging speed, which are the main factors that an imaging system should realize to broaden its application in biomedical studies.

State of the Art in Carbon Nanomaterials for Photoacoustic Imaging.

Photoacoustic imaging using energy conversion from light to ultrasound waves has been developed as a powerful tool to investigate in vivo phenomena due to their complex characteristics. In photoacoustic imaging, endogenous chromophores such as oxygenated hemoglobin, deoxygenated hemoglobin, melanin, and lipid provide useful biomedical information at the molecular level. However, these intrinsic absorbers show strong absorbance only in visible or infrared optical windows and have limited light transmission, making them difficult to apply for clinical translation. Therefore, the development of novel exogenous contrast agents capable of increasing imaging depth while ensuring strong light absorption is required. We report here the application of carbon nanomaterials that exhibit unique physical, mechanical, and electrochemical properties as imaging probes in photoacoustic imaging. Classified into specific structures, carbon nanomaterials are synthesized with different substances according to the imaging purposes to modulate the absorption spectra and highly enhance photoacoustic signals. In addition, functional drugs can be loaded into the carbon nanomaterials composite, and effective in vivo monitoring and photothermal therapy can be performed with cell-specific targeting. Diverse applied cases suggest the high potential of carbon nanomaterial-based photoacoustic imaging in in vivo monitoring for clinical research.

Review on Multispectral Photoacoustic Analysis of Cancer: Thyroid and Breast.

In recent decades, photoacoustic imaging has been used widely in biomedical research, providing molecular and functional information from biological tissues in vivo. In addition to being used for research in small animals, photoacoustic imaging has also been utilized for in vivo human studies, achieving a multispectral photoacoustic response in deep tissue. There have been several clinical trials for screening cancer patients by analyzing multispectral responses, which in turn provide metabolomic information about the underlying biological tissues. This review summarizes the methods and results of clinical photoacoustic trials available in the literature to date to classify cancerous tissues, specifically of the thyroid and breast. From the review, we can conclude that a great potential exists for photoacoustic imaging to be used as a complementary modality to improve diagnostic accuracy for suspicious tumors, thus significantly benefitting patients' healthcare.

An Enhanced Affine Projection Algorithm Based on the Adjustment of Input-Vector Number.

An enhanced affine projection algorithm (APA) is proposed to improve the filter performance in aspects of convergence rate and steady-state estimation error, since the adjustment of the input-vector number can be an effective way to increase the convergence rate and to decrease the steady-state estimation error at the same time. In this proposed algorithm, the input-vector number of APA is adjusted reasonably at every iteration by comparing the averages of the accumulated squared errors. Although the conventional APA has the constraint that the input-vector number should be integer, the proposed APA relaxes that integer-constraint through a pseudo-fractional method. Since the input-vector number can be updated at every iteration more precisely based on the pseudo-fractional method, the filter performance of the proposed APA can be improved. According to our simulation results, it is demonstrated that the proposed APA has a smaller steady-state estimation error compared to the existing APA-type filters in various scenarios.

Listening to drug delivery and responses via photoacoustic imaging.

Administrating pharmaceutic agents efficiently to achieve the therapeutic effect is the aim of all drug delivery techniques. Recent drug delivery systems aim to deliver high doses of drugs to disease sites accurately while maximizing therapeutic effects and minimizing potential side effects. Key approaches apply image guidance techniques for the quantification of drug biodistribution and pharmacokinetic parameters during drug delivery. This review highlights recent research on image-guided drug delivery systems based on photoacoustic imaging, which has been attracting attention for its non-invasiveness, non-ionizing radiation, and real-time imaging functions. Photoacoustic imaging based on the photothermal conversion efficiency of agents can be easily combined with various phototherapeutics, making them highly suitable for drug delivery therapy platforms. Here, we summarize and compare the characteristics of various types of photoacoustic imaging systems, focus on contrast-enhanced photoacoustic imaging and controlled release of therapeutics in drug delivery systems for synergistic therapies.

Review on Optical Imaging Techniques for Multispectral Analysis of Nanomaterials.

Biomedical imaging is an essential tool for investigating biological responses in vivo. Among the several imaging techniques, optical imaging systems with multispectral analysis of nanoparticles have been widely investigated due to their ability to distinguish the substances in biological tissues in vivo. This review article focus on multispectral optical imaging techniques that can provide molecular functional information. We summarize the basic principle of the spectral unmixing technique that enables the delineation of optical chromophores. Then, we explore the principle, typical system configuration, and biomedical applications of the representative optical imaging techniques, which are fluorescence imaging, two-photon microscopy, and photoacoustic imaging. The results in the recent studies show the great potential of the multispectral analysis techniques for monitoring responses of biological systems in vivo.

Photoacoustic imaging systems based on clinical ultrasound platform.

Photoacoustic imaging has drawn a significant amount of attention due to its unique capacity for functional, metabolic, and molecular imaging, which is achieved by the combination of optical excitation and acoustic detection. With both strengths of light and ultrasound, photoacoustic images can provide strong optical contrast at high ultrasound resolution in deep tissue. As photoacoustic imaging can be used to visualize complementary information to ultrasound imaging using the same data acquisition process, several studies have been conducted on combining photoacoustic imaging with existing clinical ultrasound systems. This review highlights our development of a photoacoustic/ultrasound dual-modal imaging system, various features and functionalities implemented for clinical translation, and preclinical/clinical studies performed by using the systems.

A case study on the application evaluation of integrative medical service model for the improvement of quality of life for dementia patients and caregivers.

BACKGROUND: Since 4 major diseases and geriatric diseases require consistent management, individuals with any of these diseases cannot live alone and need caregivers' assistance. Given these characteristics, an integrative medical service model for 4 major diseases and geriatric diseases was developed in Korea, currently. Dementia, one of the typical geriatric diseases, requires caregivers' assistance from the beginning because of its enormous burden. Thus, it is necessary to provide an integrative medical service that can improve the quality of life (QoL) for both patients and caregivers. Therefore, this study aims to collect various feedback by applying an integrative medical service, which was developed to improve the QoL in patients with dementia and their caregivers, to a single case, and to modify and improve the integrative medical service model based on the results. METHOD/DESIGN: The integrative medical service program, which was developed to improve the QoL in patients with dementia and their caregivers in Korea, will be used for a patient-caregiver pair. This is an observational study with quantitative and qualitative feedback from various viewpoints. The program will be conducted in 8 sessions (twice a week, within 120 minutes). The patient will receive both Western and Korean medicine, and an integrative service will be provided to improve cognitive rehabilitation and QoL. Feedback collected at each session will be reflected on the program of the subsequent session. RESULTS: This study will then modify and improve the program with feedback and provide integrative medical services to a patient with dementia and caregiver. DISCUSSION: Patients with dementia need a program that would help them maintain cognitive function, and caregivers need a program that would improve their QoL by reducing the caregiving burden. This study is unique because the developed program is performed after modification based on feedback from the previous session. Accordingly, the patient and caregiver can check which program is the most satisfactory and helpful in improving their QoL. We expect that this study can modify the integrative medical service model to the optimized patient-based model. This study can also be used as basic data for a clinical pathway development study that applies the modified model to medical institutes.

A Variable-Sampling Time Model Predictive Control Algorithm for Improving Path-Tracking Performance of a Vehicle.

This paper proposes a novel model predictive control (MPC) algorithm that increases the path tracking performance according to the control input. The proposed algorithm reduces the path tracking errors of MPC by updating the sampling time of the next step according to the control inputs (i.e., the lateral velocity and front steering angle) calculated in each step of the MPC algorithm. The scenarios of a mixture of straight and curved driving paths were constructed, and the optimal control input was calculated in each step. In the experiment, a scenario was created with the Automated Driving Toolbox of MATLAB, and the path-following performance characteristics and computation times of the existing and proposed MPC algorithms were verified and compared with simulations. The results prove that the proposed MPC algorithm has improved path-following performance compared to those of the existing MPC algorithm.

High-speed photoacoustic microscopy: A review dedicated on light sources.

In recent years, many methods have been investigated to improve imaging speed in photoacoustic microscopy (PAM). These methods mainly focused upon three critical factors contributing to fast PAM: laser pulse repetition rate, scanning speed, and computing power of the microprocessors. A high laser repetition rate is fundamentally the most crucial factor to increase the PAM speed. In this paper, we review methods adopted for fast PAM systems in detail, specifically with respect to light sources. To the best of our knowledge, ours is the first review article analyzing the fundamental requirements for developing high-speed PAM and their limitations from the perspective of light sources.

Multiparametric Photoacoustic Analysis of Human Thyroid Cancers In Vivo.

Thyroid cancer is one of the most common cancers, with a global increase in incidence rate for both genders. Ultrasound-guided fine-needle aspiration is the current gold standard to diagnose thyroid cancers, but the results are inaccurate, leading to repeated biopsies and unnecessary surgeries. To reduce the number of unnecessary biopsies, we explored the use of multiparametric photoacoustic (PA) analysis in combination with the American Thyroid Association (ATA) Guideline (ATAP). In this study, we performed in vivo multispectral PA imaging on thyroid nodules from 52 patients, comprising 23 papillary thyroid cancer (PTC) and 29 benign cases. From the multispectral PA data, we calculated hemoglobin oxygen saturation level in the nodule area, then classified the PTC and benign nodules with multiparametric analysis. Statistical analyses showed that this multiparametric analysis of multispectral PA responses could classify PTC nodules. Combining the photoacoustically indicated probability of PTC and the ATAP led to a new scoring method that achieved a sensitivity of 83% and a specificity of 93%. This study is the first multiparametric analysis of multispectral PA data of thyroid nodules with statistical significance. As a proof of concept, the results show that the proposed new ATAP scoring can help physicians examine thyroid nodules for fine-needle aspiration biopsy, thus reducing unnecessary biopsies. SIGNIFICANCE: This report highlights a novel photoacoustic scoring method for risk stratification of thyroid nodules, where malignancy of the nodules can be diagnosed with 83% sensitivity and 93% specificity.