Super High Resolution Research Articles

Improvement of image quality of dentomaxillofacial region in ultra-high resolution computed tomography: A phantom study.

The purpose of this study was to compare the image quality of ultra-high-resolution computed tomography (U-HRCT) with that of conventional multi-detector row CT (convCT) and demonstrate its usefulness in the dentomaxillofacial region. Phantoms were helically scanned with U-HRCT and convCT scanners using clinical protocols. In U-HRCT, phantoms were scanned in super-high-resolution (SHR) mode, and hybrid iterative reconstruction (HIR) and filtered-back projection (FBP) techniques were performed using a bone kernel (FC81). The FBP technique was performed using the same kernel as in convCT (reference). Two observers independently evaluated the 54 resulting images using a 5-point scale (5: excellent diagnostic image quality; 4: above average; 3: average; 2: subdiagnostic; and 1: unacceptable). The system performance function (SPF) was calculated for a comprehensive evaluation of the image quality using the task transfer function and noise power spectrum. Statistical analysis using the Kruskal-Wallis test was performed to compare the image quality among the three protocols. The observers assigned higher scores to images acquired with the SHRHIR and SHRFBP protocols than to those acquired with the reference (p < 0.0001 and p < 0.0001, respectively). The relative SPF value at 1.0 cycles/mm in SHRHIR and SHRFBP compared to the reference protocol were 151.5 and 45.6%, respectively. Through phantom experiments, this study demonstrated that U-HRCT can provide superior-quality images compared to conventional CT in the dentomaxillofacial region. The development of a better image reconstruction method is required to improve image quality and optimise the radiation dose.

Cervical CT Angiography: The Advantage of Ultra-High-Resolution CT Versus Conventional HRCT.

Pre-treatment depiction of the cervical arteries is important for better intra-arterial infusion therapy of malignant head and neck tumors. There have not been any studies on the image quality of ultra-high-resolution computed tomography (U-HRCT) for cervical CT angiography (CTA). The aim of this study is to evaluate the advantages of U-HRCT over conventional HRCT for cervical CTA; Methods: Forty-one patients underwent cervical CTA prior to selective intra-arterial infusion chemotherapy for malignant head and neck tumors. Twenty-two patients were scanned on conventional HRCT, while the remaining nineteen on U-HRCT. U-HRCT super-high-resolution (SHR) mode was used in 8 patients, while high-resolution (HR) mode was used in 11 patients. On CTA, the visibility of 18 branches from bilateral external carotid arteries was evaluated using a 5-point scale by three radiologists in consensus. Prior to the patient study, a head-neck CT phantom study regarding mock arterial density and its visibility was performed; Results: Regarding the patient study, the mean score of the SHR mode for visibility was significantly higher than that of conventional HRCT in 17 of 18 arteries (p < 0.05). The mean score of the HR mode for visibility was significantly higher than that of conventional HRCT in all arteries (p < 0.05). Regarding the phantom study, the maximum density of the SHR mode was significantly higher than that of conventional HRCT for mock proximal and peripheral arteries (p < 0.01). In addition, the visual score of the SHR mode for mock arteries was significantly higher than that of conventional HRCT (p < 0.05); Conclusions: U-HRCT provides higher image quality in terms of visualization of the arteries than conventional HRCT in cervical CTA.

Multi-scale multi-instance contrastive learning for whole slide image classification

Multi-instance learning (MIL) has become the mainstream solution for processing super-high resolution whole slide images (WSIs) with the pyramidal structure in digital pathology. Current MIL-based methods usually learn features from WSI at a specific magnification, ignoring the multi-scale information contained in the WSI and the comparative learning of global features. In addition, the lack of instance labeling can lead to weak model supervision, which may compromise the model’s ability to discriminate fine-grained features, ultimately affecting bag-level feature learning. Therefore, we propose a novel multi-scale multi-instance contrastive learning framework to learn more discriminative feature representation across scales for pathological WSI classification. The proposed method begins with a two-stream feature aggregator module, which extracts both bag embeddings and selects the representative instances simultaneously. Following the bag embedding branch, a multi-scale contrastive learning module is designed to learn the global feature comparisons of WSIs across multiple scales by leveraging its inherent pyramid structure. Additionally, based on the instances selection branch, a patch-level classifier is combined with the bag-level classifier to jointly optimize the model training process, enhancing the supervision of the model. The proposed framework is evaluated on three publicly available WSI datasets, achieving an area under the curve of 95.8%, 95.5%, and 88.2%, respectively, consistently outperforming all the compared methods including single- and multi-scale ones.

Effect of Matrix Size and Acquisition Mode on Image Quality and Radiation Dose of Ultra-High-Resolution CT of the Temporal Bone: An Anatomical Study.

Purpose: To compare image quality and radiation exposure between super- and ultra-high-resolution helical and super-high-resolution volumetric CT of the temporal bone. Methods: Six cadaveric temporal bone specimens were used to evaluate key temporal bone structures using the following CT reconstruction and acquisition modes: helical and single-volume acquisition modes in super-high resolution (0.25-mm slice thickness, 10242 matrix), and helical mode in ultra-high resolution (0.25-mm slice thickness, 20482 matrix). Two observers performed 5 previously described preoperative measurements, measured noise and signal-to-noise ratios for air, and noise for bone, and rated the visualization of 5 anatomical structures on a 4-point scale, for each reconstruction mode. Radiation dose exposure was recorded for each examination. Results: There was no significant difference between any of the quantitative or qualitative measurements in any of the reconstruction and acquisition modes. There was a slight increase in noise and a decrease in signal-to-noise ratio in the air using the single-volume mode (115 ± 13.1 HU and 8.37 ± 0.91, respectively) compared to the helicoidal super-high-resolution (92.4 ± 11.8 HU and 10.8 ± 1.26, respectively) and helicoidal ultra-high-resolution (91.1 ± 10.7 HU and 10.9 ± 1.39, respectively) modes (P < .002). The volumic CT dose index was 50.9 mGy with helical acquisition and 29.8 mGy with single-volume acquisition mode (P < .0001). Conclusion: The single-volume super-high-resolution acquisition mode allows a reduction in radiation dose exposure without compromising image quality compared to helical scanning, but with a slightly lower signal-to-noise ratio in air with the single-volume mode, while there was no difference in image quality between the helical super- and ultra-high-resolution modes.

Wavy-shaped flexible capacitive strain sensor for multiple deformations recognition

In this study, a flexible capacitive strain sensor based on a novel wavy-shaped structure for multiple deformations recognition was developed. Based on the simplified deformation of the wavy-shaped structure, the capacitive response of the sensor under both stretching and compressing deformations was analyzed. To evaluate the performance of the sensor, both stretch and compression for the sensor unit were calibrated and characterized, with results showing excellent sensitivity for both deformations. The sensor unit also exhibits super high resolution and dependable durability, which demonstrates its extraordinary sensing ability. Furthermore, by using active capacitive shielding layers, the wavy-shaped flexible strain sensor can also recognize stretching and bending deformations. Finally, the developed flexible sensor was integrated on a wearable elbow sleeve for sensing the bending angle of the elbow joint, which demonstrates its performance in rehabilitation.

Measurement of Fe emission spectrum from 170 nm to 600 nm with a coma-free spectrometer

A coma-free superhigh spectral resolution optical spectrometer was successfully designed and constructed for practical application.

Development and Test of a Multimode Piezomotor With Active Contact Force Adjusting

Piezomotors have been widely used for motion generation with long stroke and fine resolution, where stick-slip mode features a high motion velocity but a low load capacity, inchworm mode has a high load capacity but a low motion velocity, and scan mode is able to realize super-high resolution but less travel range. Combining these motion modes to achieve a well-rounded piezomotor is challengeable but significant. In this study, a piezomotor with multiple motion modes is proposed. A compliant mechanism with a parallelogram mechanism and lever-type amplifiers is designed to realize various motion modes and adjust the contact force, which has a significant impact on motion performance. To prevent the backward motion and slippage during motion, two power-function based driving signals are designed and analyzed for stick-slip mode and inchworm mode, respectively. A prototype of the designed piezomotor was fabricated to validate the feasibility. According to the experiment results, the maximum motion velocity is 3.24 mm/s, the load capacity is 7.85 N, and the most fine displacement resolution is 10 nm. The proposed methodology is applicable to other types of multi-mode piezomotors.

Applying Super High Resolution Fluorescence Microscope and Advanced Smart Cloud Algorithm in Real-Time Quantitative Processing and Analysis of Electroconvection

In an electrochemical cell at high current densities, electroconvection plays a critical role in determining the morphology of electrodeposited metals. The resultant dendrite formation leads to risky battery performance failure. Over the past decades, though intensive theoretical analysis and experimental effort have been done, the detailed structure and dynamics of electroconvection remain unknown, because experimental observations lacked the resolution to expose the fundamental, hierarchical spatial structure of these flows, while the data processing algorithms were not fully established for large sample size. To address this shortcoming, we built an advanced optical electrochemical cell that fits in situ imaging with a super-resolution fluorescence microscope. By observing and recording real-time motions of electrolytes, electroconvection flows have been interrogated at unprecedented, high temporal and spatial resolution. As a complement to the visualization studies, a cloud-computing analysis algorithm was developed by combining a higher resolution Particle Image Velocimetry algorithm and a machine learning model to enable velocity distribution data over the entire optical field of view at nanoscale or microscale spatial resolution. Consequently, detailed velocity maps are obtained across the optical electrochemical cell, allowing us to quantitatively measure and analyze the initiation and evolution of the hierarchical microstructures inside the electroconvection in a unidirectional electric field. With these powerful tools, we further studied the effect of polymer viscoelasticity on electroconvection and electrodeposition. The addition of an ultrahigh molar mass polyethylene oxide to the electrolytes transforms the materials to a viscoelastic fluid state that changes the electroconvection dependence on time and voltage and induces a smooth electrodeposition on the metal anode by unique polymer rheological properties. Especially, the relaxation of long polymer chains in electrolyte provides a promising manner to prevent dendrite growth. We further analyzed these observations using direct numerical simulations for Newtonian and viscoelastic fluid models, and the quantitative analysis of experimental results indicates good consistency with simulation predictions.

Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies.

Objective. Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better contrast, noise and spatial resolution performance compared to conventional scintillator-based systems. With multi-energy threshold detection, PCD can simultaneously provide the photon energy measurement and enable material decomposition for spectral imaging. In this work, we report a performance evaluation of our first CdZnTe-based prototype full-size PCCT system through various phantom imaging studies.Approach.This prototype system supports a 500 mm scan field-of-view and 10 mmz-coverage at isocenter. Phantom scans were acquired using 120 kVp from 50 to 400 mAs to assess the imaging performance on: CT number accuracy, uniformity, noise, spatial resolution, material differentiation and quantification.Main results.Both qualitative and quantitative evaluations show that PCCT, under the tested conditions, has superior imaging performance with lower noise and improved spatial resolution compared to conventional energy integrating detector (EID)-CT. Using projection domain material decomposition approach with multiple energy bin measurements, PCCT virtual monoenergetic images have lower noise, and good accuracy in quantifying iodine and calcium concentrations. These results lead to increased contrast-to-noise ratio (CNR) for both high and low contrast study objects compared to EID-CT at matched dose and spatial resolution. PCCT can also generate super-high resolution images using much smaller detector pixel size than EID-CT and greatly improve image spatial resolution.Significance.Improved spatial resolution and quantification accuracy with reduced image noise of the PCCT images can potentially lead to better diagnosis at reduced radiation dose compared to conventional EID-CT. Increased CNR achieved by PCCT suggests potential reduction in iodine contrast media load, resulting in better patient safety and reduced cost.

Insights into dendritic cell maturation during infection with application of advanced imaging techniques.

Dendritic cells (DCs) are crucial for the initiation and regulation of adaptive immune responses. When encountering immune stimulus such as bacterial and viral infection, parasite invasion and dead cell debris, DCs capture antigens, mature, acquire immunostimulatory activity and transmit the immune information to naïve T cells. Then activated cytotoxic CD8+ T cells directly kill the infected cells, while CD4+ T helper cells release cytokines to aid the activity of other immune cells, and help B cells produce antibodies. Thus, detailed insights into the DC maturation process are necessary for us to understand the working principle of immune system, and develop new medical treatments for infection, cancer and autoimmune disease. This review summarizes the DC maturation process, including environment sensing and antigen sampling by resting DCs, antigen processing and presentation on the cell surface, DC migration, DC-T cell interaction and T cell activation. Application of advanced imaging modalities allows visualization of subcellular and molecular processes in a super-high resolution. The spatiotemporal tracking of DCs position and migration reveals dynamics of DC behavior during infection, shedding novel lights on DC biology.

Super high resolution numerical weather prediction model simulation of tiny anticyclones observed at the Hong Kong International Airport

As a follow-up study of the observation of tiny anticyclones by short range LIDAR at the Hong Kong International Airport, super high model numerical weather prediction model simulation of the airflow is performed at a spatial resolution of 50 m. The simulation successfully captures the tiny anticyclonic flow, suggesting that such flow could partly arise from terrain effect on the airflow at the airport. The variability of the winds as observed by an anemometer and as forecast by the model compare well, suggesting that the simulations are realistic. Two case studies are considered. The results could be useful for reference by weather forecasters at the other airports in monitoring and studying terrain-disrupted airflow.

A Rapid Self-Supervised Deep-Learning-Based Method for Post-Earthquake Damage Detection Using UAV Data (Case Study: Sarpol-e Zahab, Iran)

Immediately after an earthquake, rapid disaster management is the main challenge for relevant organizations. While satellite images have been used in the past two decades for building-damage mapping, they have rarely been utilized for the timely damage monitoring required for rescue operations. Unmanned aerial vehicles (UAVs) have recently become very popular due to their agile deployment to sites, super-high spatial resolution, and relatively low operating cost. This paper proposes a novel deep-learning-based method for rapid post-earthquake building damage detection. The method detects damages in four levels and consists of three steps. First, three different feature types—non-deep, deep, and their fusion—are investigated to determine the optimal feature extraction method. A “one-epoch convolutional autoencoder (OECAE)” is used to extract deep features from non-deep features. Then, a rule-based procedure is designed for the automatic selection of the proper training samples required by the classification algorithms in the next step. Finally, seven famous machine learning (ML) algorithms—including support vector machine (SVM), random forest (RF), gradient boosting (GB), extreme gradient boosting (XGB), decision trees (DT), k-nearest neighbors (KNN), and adaBoost (AB)—and a basic deep learning algorithm (i.e., multi-layer perceptron (MLP)) are implemented to obtain building damage maps. The results indicated that auto-training samples are feasible and superior to manual ones, with improved overall accuracy (OA) and kappa coefficient (KC) over 22% and 33%, respectively; SVM (OA = 82% and KC = 74.01%) was the most accurate AI model with a slight advantage over MLP (OA = 82% and KC = 73.98%). Additionally, it was found that the fusion of deep and non-deep features using OECAE could significantly enhance damage-mapping efficiency compared to those using either non-deep features (by an average improvement of 6.75% and 9.78% in OA and KC, respectively) or deep features (improving OA by 7.19% and KC by 10.18% on average) alone.

Microwave Photonic Sensing for High Performance Displacement Measurement Based on Period-One Dynamics in a Laser

Microwave photonic (MWP) sensing and measurement are envisioned to be a promising alternate to the conventional pure electronic or optical solutions. By using a semiconductor laser (SL) subjected to external optical feedback (EOF) operating at period-one (P1) dynamic state to generate MWP signals, a high performance sensing system is proposed for displacement with wide measurement range and super-high resolution. Through analysis on the state diagram of the system and its dynamics in P1, the relationship between the P1 oscillation frequency of the system and external cavity length is determined. Further, a measurement formula for displacement sensing is worked out. Then, the relevant signal processing algorithm to retrieve displacement information is developed by considering mode-hopping, frequency-hopping, and sawtooth-like phenomena that occurred in the relationship. Both simulation and experiment results confirmed the proposed MWP sensing approach.

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reconstruction (DLR) method, as well as filtered back projection (FBP), hybrid-type iterative reconstruction (IR), and model-based IR methods, has been clinically used. The purpose of this study was to directly compare lung CT number and airway dimension evaluation capabilities of UHR-CT using different scan modes with those of MDCT with different reconstruction methods as investigated in a lung density and airway phantom design recommended by QIBA. Lung CT number, inner diameter (ID), inner area (IA), and wall thickness (WT) were measured, and mean differences between measured CT number, ID, IA, WT, and standard reference were compared by means of Tukey's HSD test between all UHR-CT data and MDCT reconstructed with FBP as 1.0-mm section thickness. For each reconstruction method, mean differences in lung CT numbers and all airway parameters on 0.5-mm and 1-mm section thickness CTs obtained with SHR and HR modes showed significant differences with those obtained with the NR mode on UHR-CT and MDCT (p < 0.05). Moreover, the mean differences on all UHR-CTs obtained with SHR, HR, or NR modes were significantly different from those of 1.0-mm section thickness MDCTs reconstructed with FBP (p < 0.05). Scan modes and reconstruction methods used for UHR-CT were found to significantly affect lung CT number and airway dimension evaluations as did reconstruction methods used for MDCT. • Scan and reconstruction methods used for UHR-CT showed significantly higher CT numbers and smaller airway dimension evaluations as did those for MDCT in a QIBA phantom study (p < 0.05). • Mean differences in lung CT number for 0.25-mm, 0.5-mm, and 1.0-mm section thickness CT images obtained with SHR and HR modes were significantly larger than those for CT images at 1.0-mm section thickness obtained with MDCT and reconstructed with FBP (p < 0.05). • Mean differences in inner diameter (ID), inner area (IA), and wall thickness (WT) measured with SHR and HR modes on 0.5- and 1.0-mm section thickness CT images were significantly smaller than those obtained with NR mode on UHR-CT and MDCT (p < 0.05).

Performance of Ultra-High-Resolution Computed Tomography in Super High-Resolution Mode at the Routine Radiation Dose: Phantom Study.

Using a chest phantom, we compared the image quality of ultra-high-resolution computed tomography (U-HRCT) images acquired in super high-resolution (SHR) and normal resolution (NR) mode and at the routine radiation dose. The detector size was 0.25 and 0.5 mm, respectively. A chest phantom was scanned on a U-HRCT scanner. The scan parameters were tube voltage 120 kV and volume CT dose index 13.0 mGy, the routine radiation dose for conventional scans. The rotation time was 0.5 s/rot, the number of matrices was 512 in NR and 1024 in SHR mode. For physical evaluation, the modulation transfer function was measured on the spherical simulated nodule, and the noise power spectrum on the cylindrical water phantom. A CT value profile curve was created using an in-house simulated bronchial phantom. For visual evaluation, 3 radiologists and 3 radiology technologists evaluated overall image quality using a 4-grade scale (grade 1, poor; and grade 4, excellent). The 10% of modulation transfer function was 13.5 lp/cm in NR and 14.9 lp/cm in SHR mode ( P <0.01). ƒ peak was 5.6 lp/cm in NR and 8.8 lp/cm in SHR mode ( P <0.01), and the peak of noise power spectrum shifted. On the profile curves, the CT value at the edge changed in NR but not in SHR mode. The overall image quality was grade 3.0 ± 0.7 in SHR and grade 2.0 ± 0.7 in NR mode ( P <0.01). The image quality of SHR mode with U-HRCT was superior to that of NR mode at the routine radiation dose.

Microscale Perovskite Quantum Dot Light‐Emitting Diodes (Micro‐PeLEDs) for Full‐Color Displays

AbstractGroup III–V semiconductor‐based microscale light‐emitting diode (micro‐LED) displays are recognized as one of the most promising display technologies with superhigh brightness and resolution, strong contrast, and superlarge color gamut but currently suffer from low efficiency, low production yield, and high cost. Here, it is proposed to realize cost‐effective and full‐color micro‐LED displays by using microscale perovskite quantum dot LEDs (micro‐PeLEDs) as emitters. Bright and uniform red‐, green‐, and blue‐emitting (RGB) micro‐PeLED arrays with each pixel size as small as 45 µm are fabricated by in situ inkjet printing a perovskite quantum dot (PeQD) emissive layer in the structure of indium tin oxide/poly(3,4‐ethylenedioxythiophene)‐poly(styrenesulfonate) (PEDOT:PSS)/poly(9‐vinylcarbazole) (PVK)/sodium dodecyl sulfate (SDS)/PeQD/1,3,5‐tris(1‐phenyl‐1H‐benzimidazol‐2‐yl)benzene (TPBi)/LiF/Al. These RGB micro‐PeLED arrays display an external quantum efficiency of 0.832%, 0.419%, and 0.052% for red, green, and blue colors, a resolution of 210 PPI, and a wide color gamut (135% of the National Television Standards Committee standard). The authors further demonstrate flexible and full‐color active‐matrix micro‐PeLED displays, which have potential applications in future ultrahigh‐definition displays, light communication, and artificial intelligence.

High-resolution magnetic resonance imaging of the triangular fibrocartilage complex using compressed sensing sensitivity encoding (SENSE)

PurposeTo evaluate the optimal sequence for high-resolution magnetic resonance imaging (MRI) of the triangular fibrocartilage complex (TFCC) using compressed sensing-sensitivity encoding (CS-SENSE). MethodsThree-dimensional fast field echo T2-weighted images were obtained from 13 healthy volunteers using the original, high spatial resolution sequence with CS-SENSE [HR (CS-SENSE)] and without CS-SENSE (HR) and super-high spatial resolution sequence with CS-SENSE [S-HR (CS-SENSE)] and without CS-SENSE (S-HR). For qualitative analysis, the number of patients affected by motion artifacts in each sequence was counted, and the visualization of the TFCC anatomic structures and overall image quality were categorized. For the quantitative analysis, relative signal intensity (SI) and relative contrast of the lunate bone marrow, lunate cartilage, and disk proper in the wrist joint were all calculated. ResultsThe HR (CS-SENSE) sequence showed better visualization scores than the original sequence in the triangular ligament at the ulnar styloid tip, dorsal radioulnar ligament, and ulnotriquetral ligament. Similarly, the S-HR (CS-SENSE) sequence showed better visualization scores than the original sequence in the triangular ligament at the ulnar styloid tip and dorsal radioulnar ligament. Overall image quality scores were not significantly different, and motion artifacts in the HR and S-HR sequences were observed in 3 of the 13 patients. In contrast, the original sequence showed higher values than those in the HR (CS-SENSE) and S-HR (CS-SENSE) sequences in relative SI of the bone marrow and relative contrast of the cartilage-bone marrow and cartilage-disk proper. ConclusionsOut of the three sequences, the HR (CS-SENSE) sequence provided the highest visualization score and diagnostically sufficient image quality score, although relative SI and relative contrast were low. The HR (CS-SENSE) sequence may be clinically useful for imaging TFCCs.

High-Resolution CT Imaging of the Temporal Bone: A Cadaveric Specimen Study.

Objective Super-high and ultra-high spatial resolution computed tomography (CT) imaging can be advantageous for detecting temporal bone pathology and guiding treatment strategies. Methods Six temporal bone cadaveric specimens were used to evaluate the temporal bone microanatomic structures utilizing the following CT reconstruction modes: normal resolution (NR, 0.5-mm slice thickness, 512 2 matrix), high resolution (HR, 0.5-mm slice thickness, 1,024 2 matrix), super-high resolution (SHR, 0.25-mm slice thickness, 1,024 2 matrix), and ultra-high resolution (UHR, 0.25-mm slice thickness, 2,048 2 matrix). Noise and signal-to-noise ratio (SNR) for bone and air were measured at each reconstruction mode. Two observers assessed visualization of seven small anatomic structures using a 4-point scale at each reconstruction mode. Results Noise was significantly higher and SNR significantly lower with increases in spatial resolution (NR, HR, and SHR). There was no statistical difference between SHR and UHR imaging with regard to noise and SNR. There was significantly improved visibility of all temporal bone osseous structures of interest with SHR and UHR imaging relative to NR imaging ( p < 0.001) and most of the temporal bone osseous structures relative to HR imaging. There was no statistical difference in the subjective image quality between SHR and UHR imaging of the temporal bone ( p ≥ 0.085). Conclusion Super-high-resolution and ultra-high-resolution CT imaging results in significant improvement in image quality compared with normal-resolution and high-resolution CT imaging of the temporal bone. This preliminary study also demonstrates equivalency between super-high and ultra-high spatial resolution temporal bone CT imaging protocols for clinical use.

Planar polarity in primate cone photoreceptors: a potential role in Stiles Crawford effect phototropism

Human cone phototropism is a key mechanism underlying the Stiles-Crawford effect, a psychophysiological phenomenon according to which photoreceptor outer/inner segments are aligned along with the direction of incoming light. However, such photomechanical movements of photoreceptors remain elusive in mammals. We first show here that primate cone photoreceptors have a planar polarity organized radially around the optical center of the eye. This planar polarity, based on the structure of the cilium and calyceal processes, is highly reminiscent of the planar polarity of the hair cells and their kinocilium and stereocilia. Secondly, we observe under super-high resolution expansion microscopy the cytoskeleton and Usher proteins architecture in the photoreceptors, which appears to establish a mechanical continuity between the outer and inner segments. Taken together, these results suggest a comprehensive cellular mechanism consistent with an active phototropism of cones toward the optical center of the eye, and thus with the Stiles-Crawford effect.

Continuous live cell imaging using dark field microscopy.

The optical observation of live cell behavior is critical for biological and biomedical studies. The development of techniques for long-term cell and tissue imaging is, however, hindered by phototoxicity induced by excited fluorophores. We, herein, propose a methodology to capture live cell behavior using dark field microscopy (DM). Since the light intensity of DM is merely ∼0.1% of bright-field microscopy (BM) and ∼0.5% of fluorescence microscopy (FM), it allows super long and frequent live cell imaging. Our results demonstrate that continuous exposure to DM light for 48 h brings about no observable effect on the growth rate of 3T3 fibroblasts and HepG2 hepatoma cells, indicating minimum photo-toxicity. Moreover, DM images show contrast comparable to FM, which does not depend on the probes and staining efficiency. We, therefore, conclude that the proposed approach is suitable for long-term live cell imaging with super-high temporal resolution.