Fast Image Acquisition Research Articles

INav-based, Automated Coronary Magnetic Resonance Angiography for the Detection of Coronary Artery Stenosis (iNav-AUTO CMRA)

BackgroundCoronary computed tomography angiography (CCTA) is recommended as the first line diagnostic imaging modality in low to intermediate risk individuals suspected of stable coronary artery disease (CAD). However, CCTA exposes patients to ionising radiation and potentially nephrotoxic contrast agents. Invasive coronary angiography (ICA) is the gold-standard investigation to guide coronary revascularisation strategy, however, invasive procedures incur an inherent risk to the patient. Coronary magnetic resonance angiography (Coronary MRA) avoids these issues. Nevertheless, clinical implementation is currently limited due to extended scanning durations, inconsistent image quality, and consequent lack of diagnostic accuracy. Several technical Coronary MRA innovations including advanced respiratory motion correction with 100% scan efficiency (no data rejection), fast image acquisition with motion-corrected undersampled image reconstruction and deep-learning (DL)-based automated planning have been implemented and now await clinical validation in multi-centre trials. MethodsThe objective of the iNav-AUTO CMRA prospective multi-centre study is to evaluate the diagnostic accuracy of a newly developed, state-of-the-art, standardised, and automated Coronary MRA framework compared to CCTA in 230 patients undergoing clinical investigation for CAD. The study protocol mandates the administration of oral beta-blockers to decrease heart rate to below 60bpm and the use of sublingual nitroglycerine spray to induce vasodilation. Additionally, the study incorporates the utilisation of standardised postprocessing with sliding-thin-slab multiplanar reformatting, in combination with evaluation of the source images, to optimize the visualisation of coronary artery stenosis. DiscussionIf proven effective, Coronary MRA could provide a non-invasive, needle-free, yet also clinically viable, alternative to CCTA. Trial RegistrationThis study is registered at clinicaltrials.gov (NCT05473117).

Advancements in Dental Imaging: A Technological Renaissance in Diagnosis and Treatment Planning

Dental imaging technology has undergone significant advancements in recent years, offering dentists unprecedented tools for accurate diagnosis and treatment planning. This article provides a comprehensive overview of the latest innovations in dental imaging and their clinical applications. Cone Beam Computed Tomography (CBCT) has revolutionized imaging by providing high-resolution 3D images with minimal radiation exposure. Its versatility in applications, from implant planning to TMJ analysis, makes it an indispensable tool in modern dentistry. Studies have shown its effectiveness in detecting root fractures and periapical lesions, enhancing diagnostic precision. Digital Radiography has replaced traditional film-based systems, offering benefits like reduced radiation doses and faster image acquisition. Its superior diagnostic capabilities in detecting caries and periodontal conditions enable early intervention and preventive strategies, improving patient outcomes. Intraoral Scanners have transformed impression-taking, eliminating the need for messy materials and improving patient comfort. Their accuracy in capturing detailed intraoral structures ensures precise fit and aesthetics in crown and bridge restorations, enhancing overall treatment quality. Optical Coherence Tomography (OCT) has gained attention for its non-invasive, high-resolution imaging of dental tissues. Its utility in detecting early caries lesions, evaluating periodontal tissues, and assessing adhesive interfaces in restorations supports conservative treatment approaches and long-term restoration success. Artificial Intelligence (AI) algorithms are being integrated into dental imaging, enhancing diagnostic capabilities and streamlining workflow. AI’s role in image analysis, risk assessment, and treatment planning opens avenues for personalized dentistry and predictive outcomes, ultimately improving patient care. In conclusion, the rapid advancements in dental imaging technologies have transformed dental diagnostics and treatment planning. Integrating these innovations into clinical practice not only improves diagnostic accuracy and treatment outcomes but also enhances patient experience and satisfaction. Continued research and technological advancements promise further enhancements in dental imaging capabilities, paving the way for optimized patient care in the future.

Improved Magnetic Resonance Image Reconstruction using Compressed Sensing and Adaptive Multi Extreme Particle Swarm Optimization Algorithm

One powerful technique that can offer a thorough examination of the body's internal structure is magnetic resonance imaging (MRI). MRI's lengthy acquisition times, however, may restrict its clinical usefulness, particularly in situations where time is of the essence. Compressed sensing (CS) has emerged as a potentially useful method for cutting down on MRI acquisition times; nevertheless, the effectiveness of CS-MRI is dependent on the selection of the sparsity-promoting algorithm and sampling scheme. This research paper presents a novel method based on adaptive multi-extreme particle swarm optimization (AMEPSO) and dual tree complex wavelet transform (DTCWT) for fast image acquisition in magnetic resonance. The method uses AMEPSO in order to maximize the sampling pattern and minimize reconstruction error, while also exploiting the sparsity of MR images in the DTCWT domain to improve directional selectivity and shift invariance. MATLAB software was used for simulation of the proposed method. In comparison with the particle swarm optimized-DTCWT (PSODTCWT) and DTCWT algorithms, respectively, the results demonstrated an improvement in the peak signal-to-noise ratio of 8.92% and 15.92% and a higher structural similarity index measure of 3.69% and 7.5%. Based on these improvements, the proposed method could potentially make high-quality, real-time MRI imaging possible, which might improve detection and treatment of medical conditions and increase the throughput of MRI machines.

Reconstruction of 3D knee MRI using deep learning and compressed sensing: a validation study on healthy volunteers.

To investigate the potential of combining compressed sensing (CS) and artificial intelligence (AI), in particular deep learning (DL), for accelerating three-dimensional (3D) magnetic resonance imaging (MRI) sequences of the knee. Twenty healthy volunteers were examined using a 3-T scanner with a fat-saturated 3D proton density sequence with four different acceleration levels (10, 13, 15, and 17). All sequences were accelerated with CS and reconstructed using the conventional and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using seven criteria on a 5-point-Likert-scale (overall impression, artifacts, delineation of the anterior cruciate ligament, posterior cruciate ligament, menisci, cartilage, and bone). Using mixed models, all CS-AI sequences were compared to the clinical standard (sense sequence with an acceleration factor of 2) and CS sequences with the same acceleration factor. 3D sequences reconstructed with CS-AI achieved significantly better values for subjective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.001). The images reconstructed with CS-AI showed that tenfold acceleration may be feasible without significant loss of quality when compared to the reference sequence (p ≥ 0.999). For 3-T 3D-MRI of the knee, a DL-based algorithm allowed for additional acceleration of acquisition times compared to the conventional approach. This study, however, is limited by its small sample size and inclusion of only healthy volunteers, indicating the need for further research with a more diverse and larger sample. DRKS00024156. Using a DL-based algorithm, 54% faster image acquisition (178s versus 384s) for 3D-sequences may be possible for 3-T MRI of the knee. • Combination of compressed sensing and DL improved image quality and allows for significant acceleration of 3D knee MRI. •DL-based algorithm achieved better subjective image quality than conventional compressed sensing. •For 3D knee MRI at 3 T, 54% faster image acquisition may be possible.

Development of a Fast in Situ Scanning Tunneling Microscope for Studies of Electrocatalyst Surfaces

The atomic-scale understanding of processes at the interface between solid electrodes and liquid electrolytes is of high importance for electrochemical energy storage and conversion. Electrochemical scanning tunneling microscopy (ECSTM) is a key technique for the investigation of these interfaces and as such, it has seen widespread use. However, the image acquisition in a conventional ECSTM is a rather slow process, requiring tens of seconds or minutes per image. To help understand the precise reaction mechanisms of atomic and molecular species at solid-liquid interfaces, their movement and interactions need to be resolved. For this, much higher imaging rates are necessary. High-speed STMs (video STMs) are capable of operating at rates >10 images per second, which is sufficiently fast to observe and quantitatively study a wide range of surface dynamic processes, e.g., surface diffusion and growth [1]. However, this technique has not been widely employed, mainly because of the instrumental requirements.The development of an STM for fast in situ measurements poses a set of challenges, which require a carefully planned implementation. For operation in electrochemical environment, the potentials of both STM tip and sample need to be controlled and electrochemical currents at the tip need to be kept way below the tunneling current. Fast image acquisition requires a scanner with high mechanical stability to avoid the excitation of uncontrolled tip oscillations at its resonance frequencies. Additionally, high-bandwidth measurement and control electronics and a sophisticated control software with fast scan generation and data processing capabilities are essential. No commercial system that is capable of fulfilling these requirements exists up to now. For this reason, all existing video-rate STM studies have been performed with home-built setups that employ highly specialized hardware that is not easy to reproduce.In this contribution, we present a new ECSTM developed and built in our group. The setup is based on a Nanonis SPM controller by SPECS and a custom scanner, bipotentiostat, and coarse approach control that were integrated into this system. We show example data and images to demonstrate the performance of the STM. Furthermore, we reveal the modifications employed to make it capable of video-rate imaging. These include a novel scanner design with two independent piezo stacks for slow and high-speed movements and a custom high-bandwidth preamplifier integrated into the scan head as close as possible to the tip. Fast data acquisition is realized by an FPGA-based control software, which features a user-friendly frontend and a backend with good performance even at high image acquisition rates. This software is designed to run alongside the commercial control software for the slow STM operation so that switching between the slow and fast imaging modes is as frictionless as possible. We will show preliminary test results of the early implementation of the fast imaging mode.[1] O. M. Magnussen, Chem. Eur. J. 2019, 25, 12865.

Accuracy and Feasibility of Three-Dimensional Ultrasound Testing in Eye Clinic and Emergency Department Patients with Vision Complaints

BackgroundOcular emergencies comprise 2–3% of emergency department (ED) visits, with retinal detachment requiring emergency surgery. Two-dimensional ultrasound is a rapid bedside tool but is highly operator dependent. ObjectiveWe determined three-dimensional ultrasound (3DUS) feasibility, acceptability, and usability in eye pathology detection using the ophthalmologist examination as reference standard. MethodsWe performed a prospective, blinded cohort study of a 3DUS-enabling device in 30 eye clinic and ED patients with visual symptoms and calculated 3DUS performance characteristics. Two expert readers interpreted the 3DUS images for pathology. All participants completed surveys. Results3DUS sensitivity was 0.81, specificity 0.73, positive predictive value 0.54, negative predictive value 0.91, and likelihood ratio (LR)+/LR− 3.03 and 0.26, respectively. Novice and expert sonographers had “substantial” agreement in correct diagnosis of abnormal vs. normal (κ = 0.68, 95% confidence interval 0.48–0.88). Most patients indicated that 3DUS is fast, comfortable, helps them understand their problem, and improves provider interaction/care, and all sonographers agreed; 4/5 sonographers felt confident performing ultrasound. Expert readers correctly identified an abnormal eye in 83/120 scans (76%) and correct diagnosis in 72/120 scans (65%), with no statistical difference between novice (79%; 69%) and expert (72%; 61%) sonographers (p = 0.39, p = 0.55), suggesting reduced operator dependence. Reader diagnosis confidence and image quality varied widely. Image acquisition times were fast for novice (mean 225 ± 83 s) and expert (201 ± 51) sonographers, with fast expert reader interpretation times (225 ± 136). ConclusionsA 3DUS-enabling device demonstrates a sensitivity of 0.81 and specificity of 0.73 for disease detection, fast image acquisition, and may reduce operator dependence for detecting emergent retinal pathologies. Further technological development is needed to improve diagnostic accuracy in identifying and characterizing retinal pathology.

Autoignition Characterization of Hydrogen Directly Injected into a Constant-Volume Combustion Chamber through a Heavy-Duty Injector

One factor limiting the exploitation of hydrogen as a fuel in internal combustion engines is their tendency to autoignition. In fact, on one hand, its low activation energy facilitates autoignition even with low compression ratios; on the other hand, this can become uncontrollable, due, for instance, to the presence of hot spots in the combustion chamber or to the collision of hydrogen on close surfaces. This represents a limit to the use of hydrogen at medium–high loads, therefore limiting the power density of the engine. In this work, hydrogen was injected at a pressure ranging between 15 and 25 bars into a constant-volume combustion chamber in which the temperature and pressure were increased by means of a previous combustion event. The phenomena taking place after hydrogen injection were observed through fast image acquisition and characterized by measuring the chamber pressure and temperature. In particular, ignition sites were established. The physical system was also modeled in Ansys Fluent environment, and the injection and mixture formation were simulated in order to evaluate the thermo-fluid dynamic field inside the combustion chamber just before autoignition.

Optical-scanning evanescent sensor for high-speed broadband photoacoustic microscopy

Photoacoustic microscopy with high spatial resolution and fast imaging acquisition allows observing dynamic processes of optical absorption-based microanatomic structures in three dimensions. An evanescent sensor accesses ultrasonic detection with high sensitivity and broad bandwidth while suffering from limited field of view (FOV), thus compromising the photoacoustic imaging acquisition rate. Here, we develop an optical-scanning evanescent sensor by fast deflection of the interrogation light along the interface of prism and water using a one-dimensional galvanometer, demonstrating excellent detection sensitivity of ∼132 Pa with a broadband frequency response of >140-MHz at an enlarged FOV of ∼2.90 × 0.19 mm2. Incorporating the optical-scanning evanescent sensor in photoacoustic microscopy, a volumetric image (∼3.0 × 0.25 × 1.0 mm3) with micrometer-scale spatial resolution is acquired within ∼2.5 s by synergistically scanning both photoacoustic illumination laser and sensor's interrogation light. High-speed imaging of flowing microparticles within a capillary tube offers the visualizations of the traveling processes in three dimensions. Potentially, the optical-scanning evanescent sensor allows photoacoustic microscopy accommodating to dynamic imaging at cellular level such as in vivo flow cytometry of circulating tumor cells.

Fast optical coherence tomography angiography image acquisition and reconstruction pipeline for skin application.

Traditional high-quality OCTA images require multi-repeated scans (e.g., 4-8 repeats) in the same position, which may cause the patient to be uncomfortable. We propose a deep-learning-based pipeline that can extract high-quality OCTA images from only two-repeat OCT scans. The performance of the proposed image reconstruction U-Net (IRU-Net) outperforms the state-of-the-art UNet vision transformer and UNet in OCTA image reconstruction from a two-repeat OCT signal. The results demonstrated a mean peak-signal-to-noise ratio increased from 15.7 to 24.2; the mean structural similarity index measure improved from 0.28 to 0.59, while the OCT data acquisition time was reduced from 21 seconds to 3.5 seconds (reduced by 83%).

Radiotherapy delivery error detection with electronic portal imaging device (EPID)-based in vivo dosimetry.

Radiotherapy delivery error detection with electronic portal imaging device (EPID)-based in vivo dosimetry.

Large-scale interrogation of retinal cell functions by 1-photon light-sheet microscopy

Visual processing in the retina depends on the collective activity of large ensembles of neurons organized in different layers. Current techniques for measuring activity of layer-specific neural ensembles rely on expensive pulsed infrared lasers to drive 2-photon activation of calcium-dependent fluorescent reporters. We present a 1-photon light-sheet imaging system that can measure the activity in hundreds of neurons in the exvivo retina over a large field of view while presenting visual stimuli. This allows for a reliable functional classification of different retinal cell types. We also demonstrate that the system has sufficient resolution to image calcium entry at individual synaptic release sites across the axon terminals of dozens of simultaneously imaged bipolar cells. The simple design, large field of view, and fast image acquisition make this a powerful system for high-throughput and high-resolution measurements of retinal processing at a fraction of the cost of alternative approaches.

KVM Terminal Software Design Based on RK3399 Processor

KVM denotes the initials of the keyboard, monitor and mouse of a computer. digital KVM systems are composed of two parts, one is the device terminal and the other is the software adapted to this device terminal. KVM systems are emerging remote centralized management technologies for multiple devices in multiple locations based on IP networks in recent years [1,2]. digital KVM systems mainly use IP networks to control remote computers to control remote computers mainly through IP networks [3]. Therefore, KVM systems are widely used in computer management and remote control of computers. In practical applications, the compression efficiency of images is relatively low and the delay of mouse movements is relatively large. To address these two shortcomings, this paper designs a software based on the RK3399 processor, which on the one hand performs fast image acquisition and high-quality encoding, and on the other hand realizes input control of the target computer through the mouse and keyboard control chip UI012.

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

Personal identification using analysis of the internal and external characteristics of the human finger is currently an intensively developed topic. The work in this field concerns new methods of feature extraction and image analysis, mainly using modern artificial intelligence algorithms. However, the quality of the data and the way in which it is obtained determines equally the effectiveness of identification. In this article, we present a novel device for extracting vision data from the internal as well as external structures of the human finger. We use spatially selective backlight consisting of NIR diodes of three wavelengths. The fast image acquisition allows for insight into the pulse waveform. Thanks to the external illuminator, images of the skin folds of the finger are acquired as well. This rich collection of images is expected to significantly enhance identification capabilities using existing and future classic and AI-based computer vision techniques. Sample data from our device, before and after data processing, have been shared in a publicly available database.

Selective plane illumination optical endomicroscopy with polymer imaging fibers

Imaging fibers are used to perform real-time fluorescence endomicroscopy, in vivo, in situ, with the goal of increasing diagnostic information for a plethora of organ systems and diseases. Widefield fiber endomicroscopy systems are simple, cost-effective, and come with fast image acquisition times. However, alternative approaches such as scanning systems produce higher contrast images with intrinsic optical sectioning, improving the visibility of histological features, albeit at the expense of simplicity, cost, and acquisition rate. We developed a selective plane illumination microscopy endoscopic fiber platform, consisting of an ultrafast laser fabricated end-cap, integrated with a polymer coherent fiber bundle, and an epifluorescence microscope. Polymer fibers are known to fluoresce when pumped with blue light, enhancing the background and noise in images. Our end-cap design circumvents this challenge. We demonstrate a reduction of out-of-focus features, along with improved contrast of in-focus features, in images of a tissue phantom. Moreover, we demonstrate the utility of our platform for endomicroscopy using a whole, ex vivo human lung model.

3D Cinematic Volume-Rendering Technique of Traumatic Spine Injuries: A Powerful Tool for Radiology Education

Spine trauma represents a common indication for imaging in the emergency department. Multidetector CT imaging, with its advantage of multiplanar reconstructions and fast image acquisition, is the technique of choice in the initial assessment of a patient with polytrauma. While many simple spinal fractures are adequately evaluated on 2D multiplanar reconstruction images, more complex, potentially displaced fracture patterns can be more fully highlighted on 3D reconstructions. Compared with conventional volume-rendering techniques, cinematic rendering uses a complex illumination model to create a more photorealistic representation of the fracture patterns, images that are certain to excite both trainees and clinicians. This review demonstrates the educational value and clinical utility of 3D cinematic rendering images in understanding complex spinal column injuries.Learning Objective: To demonstrate the methodology, clinical applicability, and educational utility behind 3D photorealistic cinematic rendering images of spine injuries, with emphasis on the “tension bands” biomechanical concept

Separating neuronal activity and systemic low-frequency oscillation related BOLD responses at nodes of the default mode network during resting-state fMRI with multiband excitation echo-planar imaging

Functional magnetic resonance imaging (fMRI) evaluates brain activity using blood oxygenation level-dependent (BOLD) contrast. Resting-state fMRI (rsfMRI) examines spontaneous brain function using BOLD in the absence of a task, and the default mode network (DMN) has been identified from that. The DMN is a set of nodes within the brain that appear to be active and in communication when the subject is in an awake resting state. In addition to signal changes related to neural activity, it is thought that the BOLD signal may be affected by systemic low-frequency oscillations (SysLFOs) that are non-neuronal in source and likely propagate throughout the brain to arrive at different regions at different times. However, it may be difficult to distinguish between the response due to neuronal activity and the arrival of a SysLFO in specific regions. Conventional single-shot EPI (Conv) acquisition requires a longish repetition time, but faster image acquisition has recently become possible with multiband excitation EPI (MB). In this study, we evaluated the time-lag between nodes of the DMN using both Conv and MB protocols to determine whether it is possible to distinguish between neuronal activity and SysLFO related responses during rsfMRI. While the Conv protocol data suggested that SysLFOs substantially influence the apparent time-lag of neuronal activity, the MB protocol data implied that the effects of SysLFOs and neuronal activity on the BOLD response may be separated. Using a higher time-resolution acquisition for rsfMRI might help to distinguish neuronal activity induced changes to the BOLD response from those induced by non-neuronal sources.

Recovering mixtures of fast-diffusing states from short single-particle trajectories.

Single-particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we investigated methods inspired by Bayesian nonparametrics to infer distributions of state parameters from SPT data with short trajectories, variable localization precision, and absence of prior knowledge about the number of underlying states. We discuss the advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.

Focus on lasers, imaging, microscopy, and photonics

Focus on lasers, imaging, microscopy, and photonics

Assessment of angle-dependent spectral distortion to develop accurate hyperspectral endoscopy

Hyperspectral endoscopy has shown its potential to improve disease diagnosis in gastrointestinal tracts. Recent approaches in developing hyperspectral endoscopy are mainly focusing on enhancing image speed and quality of spectral information under a clinical environment, but there are many issues in obtaining consistent spectral information due to complicated imaging conditions, including imaging angle, non-uniform illumination, working distance, and low reflected signal. We quantitatively investigated the effect of imaging angle on the distortion of spectral information by exploiting a bifurcated fiber, spectrometer, and tissue-mimicking phantom. Spectral distortion becomes severe as increasing the angle of the imaging fiber or shortening camera exposure time for fast image acquisition. Moreover, spectral ranges from 450 to 550 nm are more susceptible to the angle-dependent spectral distortion than longer spectral ranges. Therefore, imaging angles close to normal and longer target spectral ranges with enough detector exposure time could minimize spectral distortion in hyperspectral endoscopy. These findings will help implement clinical HSI endoscopy for the robust and accurate measurement of spectral information from patients in vivo.

Multi-threshold splitting tree algorithm to reduce the number of filters in programmable hyperspectral imaging for fast multi-target classification.

Programmable hyperspectral imaging is a promising and efficient technique for fast target classification by coding hyperspectral post-processing algorithms as spectral transmittances, which enables such post-processing to be directly performed by special optical dispersive element during the process of optical imaging. Compared with conventional hyperspectral imaging and post-processing techniques, it shows significant advantages of fast image acquisition, post-processing free, and a much lower load of data transmission and storage. However, when multi-target classification tasks are encountered, the speed would decrease seriously due to the requirement of a large number of filters. In this study, a novel splitting strategy is proposed to reduce the number of filters in programmable hyperspectral imaging for fast multi-target classification while maintaining the classification performance. Numerical simulation experiments were performed on six publicly available hyperspectral data sets. Compared with the conventional splitting strategies, the proposed splitting strategy can reduce the number of filters by 25% to 80% and achieve similar classification performance, which is of great significance to improve the speed of multi-target classification with programmable hyperspectral imaging technique.