8-bit Grayscale Research Articles

Watermarking method based on double-threshold correspondence imaging with lossless host image

Abstract A watermarking method based on double-threshold correspondence imaging (DTCI) with lossless host image is proposed, which employ every bit of the 8-bit grayscale host image without changing picture. This image watermarking method firstly processes the host image to obtain symbolic attribute arrays (SAAs). Then the watermark image is performs DTCI operations to rearrange the order of the speckle patterns according to the SAAs. Because there is not any additional information embedded into the host image, it ensures the watermark image with not only complete imperceptibility but also a significant capacity. When the authorized users utilize both the binary numbers of host image and the rearranged speckle patterns as the key, the watermark image can be easily retrieved. Additionally, the suggested method demonstrates remarkable robustness in the face of ‘Salt and Pepper’ noise and cropping attacks.

Orbital-angular-momentum-dependent speckles for spatial mode sorting and demultiplexing

Characterizing the orbital-angular-momentum (OAM) modes is critically important for OAM-encoded data transfer. However, traditional characterizing approaches rely on either complex and precise experimental configurations or complicated prior information processing. In these scenarios, the correlation features of OAM-dependent speckles from the scattering effect have received little attention. Here, we investigate the cross-correlation characteristics of the OAM speckles resulting from a scattering medium and propose an appealing alternative for spatial mode sorting and demultiplexing based on the OAM-dependent speckles. We demonstrate theoretically and experimentally that the cross-correlation operation between two different OAM-dependent speckles can uniformly derive an annulus pattern, whose dimension is determined by the absolute topological charge difference value between the two corresponding OAM modes. Based on this mechanism, the original coherent OAM modes can be easily sorted by implementing the cross-correlation operation between incoherently measured OAM-dependent speckles. To fully capitalize on the orthogonal feature of the OAM-dependent speckles, we also construct OAM mode demultiplexing experiments using a ground glass diffuser, where both 8-bit grayscale and 24-bit RGB OAM-encoded data demultiplexing are successfully demonstrated with superior error rates. Results show that the OAM-dependent speckles, previously treated as a nuisance for practical applications, can be surprisingly utilized as a competitive candidate for OAM mode sorting and demultiplexing, thus opening new directions in optical communication and information processing.

Image-centric compression of protein structures improves space savings

BackgroundBecause of the rapid generation of data, the study of compression algorithms to reduce storage and transmission costs is important to bioinformaticians. Much of the focus has been on sequence data, including both genomes and protein amino acid sequences stored in FASTA files. Current standard practice is to use an ordinary lossless compressor such as gzip on a sequential list of atomic coordinates, but this approach expends bits on saving an arbitrary ordering of atoms, and it also prevents reordering the atoms for compressibility. The standard MMTF and BCIF file formats extend this approach with custom encoding of the coordinates. However, the brand new Foldcomp tool introduces a new paradigm of compressing local angles, to great effect. In this article, we explore a different paradigm, showing for the first time that image-based compression using global angles can also significantly improve compression ratios. To this end, we implement a prototype compressor ‘PIC’, specialized for point clouds of atom coordinates contained in PDB and mmCIF files. PIC maps the 3D data to a 2D 8-bit greyscale image and leverages the well developed PNG image compressor to minimize the size of the resulting image, forming the compressed file.ResultsPIC outperforms gzip in terms of compression ratio on proteins over 20,000 atoms in size, with a savings over gzip of up to 37.4% on the proteins compressed. In addition, PIC’s compression ratio increases with protein size.ConclusionImage-centric compression as demonstrated by our prototype PIC provides a potential means of constructing 3D structure-aware protein compression software, though future work would be necessary to make this practical.

An adaptive enhancement method for generic multi-modal high‐bit RAW grayscale image displaying on low-bit monitors

Aiming at the poor adaptability and robustness of existing pseudo-color methods, most of which can only deal with an 8-bit grayscale, an adaptive enhancement algorithm of high grayscale images based on priori knowledge was proposed. Firstly, aiming at the problem that the original RGB color space is not easy to adjust dynamically, the power adjustment was integrated into the constructed high-bit chromatogram, and a power adaptive adjustment function based on the brightness priority over the original grayscale image was designed. Secondly, aiming at the problems of over-exposure, under-exposure, and poor gradients in RGB space, an adaptive grayscale correction algorithm was designed according to the priori knowledge distribution of RGB perceived brightness. Finally, to guarantee the color balance of the enhanced image, a color balance correction algorithm based on CMY space was designed. To verify the effectiveness of this method, it was applied to the pseudo-color enhancement of 16-bit pipeline CR images, 14-bit infrared images, 24-bit pipeline DR weld images, 8-bit or 24-bit rail crack images, and 16-bit remote sensing images respectively. The subjective and objective experimental results show that the design method has stronger adaptability, which has obvious advantages compared with the existing advanced high grayscale image enhancement methods. The enhancement effect is more coordinated, the processing result is more in line with human visual perception, and the details and texture information of the original image can be better preserved.

(132) Histometric Measurement of CD117 and PGP9.5 Immunopositive Staining in Excised Vestibular Specimens from Patients with Neuroproliferative Vestibulodynia

Abstract Introduction In 2004, Bornstein reported using immunohistochemical (IHC) analysis of stained sections of vestibular specimens, defining diagnostic criteria for neuroproliferative vestibulodynia (NPV). Criteria included presence of 8 or more mast cells manually counted in a standardized microscopic field or finding total area of subepithelial nerve fibers was 10 times higher than controls. Replicating such criteria is difficult, in part, because of variability in manual counting, IHC staining and magnification. A more reproducible methodology may be estimating percentage of immunopositive stained area using computer-assisted histometry. Objective Utilizing both manual counting and computer-assisted histometry measurements using ImageJ at a standardized magnification in specimens from vestibulectomy and control tissue published in the literature. Methods Tissue samples were collected from 17 patients with NPV. Samples were stained with CD117, a marker of mast cells, and PGP9.5, a marker of nerve endings. Twenty-five photomicrographs were each obtained using 200x and 400x magnification and all were analyzed using ImageJ. Images were converted to 8-bit grayscale and threshold manually adjusted to measure immunohistochemically stained tissue with three measurements averaged. Averages and variability between measurements in each photomicrograph and from each patient were determined. This methodology was also applied to images of tissues from patients with and without NPV (Tympanidis 2003; Goetsch 2010). For comparison, the method of analysis by manually counting CD117 immunopositive cells, described by Bornstein et al, was applied to our tissue samples by an independent observer. Clusters of immunopositive granules positively stained and separated from an adjacent cell membrane were counted as a single immunopositive cell. Results Using Image J, tissues stained with CD117 averaged 2107 ± 1339 μm2 of immunostained area, representing 0.68 ± 0.38% (range = 0.11 – 1.15%) of total area analyzed. Tissues stained with PGP9.5 averaged 1123 ± 695 μm2 of immunostained area, representing 0.40 ± 0.27% (range = 0.34 – 1.81%) of total area analyzed. Standard deviations of repeated measurements for the same area within a tissue section ranged from 0.04 – 0.7% (mean = 0.17%) for CD117 immunostaining and 0.01 – 0.78% (mean = 0.10%) for PGP 9.5. Counting cells, CD117 stained tissue averaged 30.6 ± 15.3 (range = 12 – 72) immunopositive cells per standardized field (200x magnification). These are all greater than the 8 mast cells per standardized field reported by Bornstein. In PGP9.5-stained tissue, immunostained area was 2.6-fold greater than that reported by Bornstein for controls (425 μm2). Applying our methodology to photomicrographs from Goetsch and Tympanidis, 2.48% and 2.87% of the control areas were immunopositive. Tissues from control patients without vestibulodynia had 8-fold lower (0.31%, from Goetsch) and 6.4-fold lower (0.45%, from Tympanidis) immunostained area than tissues from vestibulodynia patients using computer-assisted histometry. Conclusions NPV is a diagnosis of exclusion without routine pathology confirmation. Our 17 patients had increased density of CD117-immunopositive cells and increased PGP9.5-immunopositive nerves, confirming their NPV diagnosis. To facilitate more consistent, widespread and rapid quantification of staining, we propose using computer-assisted histometry for future studies. Disclosure No

Abstract 5388: A unified computational pathology method to quantify HER2 expression from raw IHC and IF images in breast cancer

Abstract Background: The development of automated quantitative methods to measure biomarker expression such as HER2 aims at reducing the subjective variability of pathologist-performed biomarker assessment of immunohistochemically (IHC) stained tissue slides. As an example, the deep learning-based Quantitative Continuous Scoring (QCS) algorithm [1] enables the objective measurement of biomarker expression based on the detection of individual tumor cells in the tumor regions and - for each cell, on the instance segmentation of its nucleus, cytoplasm, and membrane compartments. Methods: In order to extend the QCS image analysis to similarly analyze tissue slides stained with immunofluorescence (IF), we re-trained the fully supervised deep-learning models, adjusted the normalization of images on tissue controls to account for variability between different staining batches, and finally used the normalized signal in IF instead of the Optical Density (OD) signal in IHC as a 8-bit grayscale image on which the biomarker expression is estimated. We performed QCS on HER2 IF images (HER2 clone 29D8 [CST], imaged with Vectra [Akoya] in parallel with HER2 IHC clone 4B5 [Roche Tissue Diagnostics]) performed on 26 primary and metastatic breast cancer samples representing the full range of HER2 expression, from null to highly overexpressed. Results: Our analysis demonstrated that the QCS-based scoring on IHC-HER2 images correlates with the QCS-based scoring on IF-HER2 images. We observed a Pearson correlation of R=0.92 between the median membrane OD in IHC and the median normalized membrane signal in IF. Defining a positive cell as having an estimated membrane expression higher than a given so-called positivity threshold, we found a median Pearson correlation of R=0.85 between the percentage of positive cells detected in IHC and the percentage of positive cells detected in IF for increasing values of positivity thresholds. Correlation of the QCS median normalized membrane signal in IF was R=0.91 with mRNA (ERBB2 transcript levels [Nano String]) and R=0.88 with IHC-based H-scores, against R=0.83 and R=0.87 respectively for the QCS median membrane OD signal in IHC. Conclusion: We describe the extension of a computational pathology-based approach for biomarker quantification in IHC to IF stained tissue slides. The consistency of the image analysis method translates into the consistency of the measurements in the two imaging methods. The use of IF could enable the improved quantification of expression, co-localization and spatial distribution of multiple proteins on the tissue sample.

Application of a light-weighted convolutional neural network for automatic recognition of coal workers' pneumoconiosis in the early stage

Objective: To construct and verify a light-weighted convolutional neural network (CNN), and explore its application value for screening the early stage (subcategory 0/1 and stage Ⅰ of pneumoconiosis) of coal workers' pneumoconiosis (CWP) from digital chest radiography (DR) . Methods: A total of 1225 DR images of coal workers who were examined at an Occupational Disease Prevention and Control Institute in Anhui Province from October 2018 to March 2021 were retrospectively collected. All DR images were collectively diagnosed by 3 radiologists with diagnostic qualifications and gave diagnostic results. There were 692 DR images with small opacity profusion 0/- or 0/0 and 533 DR images with small opacity profusion 0/1 to stage Ⅲ of pneumoconiosis. The original chest radiographs were preprocessed differently to generate four datasets, namely 16-bit grayscale original image set (Origin16), 8-bit grayscale original image set (Origin 8), 16-bit grayscale histogram equalized image set (HE16) and 8-bit grayscale histogram equalized image set (HE8). The light-weighted CNN, ShuffleNet, was applied to train the generated prediction model on the four datasets separately. The performance of the four models for pneumoconiosis prediction was evaluated on a test set containing 130 DR images using measures such as the receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, and Youden index. The Kappa consistency test was used to compare the agreement between the model predictions and the physician diagnosed pneumoconiosis results. Results: Origin16 model achieved the highest ROC area under the curve (AUC=0.958), accuracy (92.3%), specificity (92.9%), and Youden index (0.8452) for predicting pneumoconiosis, with a sensitivity of 91.7%. And the highest consistency between identification and physician diagnosis was observed for Origin16 model (Kappa value was 0.845, 95%CI: 0.753-0.937, P<0.001). HE16 model had the highest sensitivity (98.3%) . Conclusion: The light-weighted CNN ShuffleNet model can efficiently identify the early stages of CWP, and its application in the early screening of CWP can effectively improve physicians' work efficiency.

Optically heated blackbody emitter for dynamic infrared scene generation

The infrared image conversion chip based on optical heating technique has advantages of wide spectral range and high spatial resolution, which is appropriate as an infrared target simulator. At present, the dynamic infrared image, which is physically generated by infrared target simulator, can achieve 8-bit grayscale level with 100 Hz refresh rate. In this paper, we demonstrate an optically heated blackbody emitter (OHBE) for dynamic infrared scene generation to further improve the grayscale level of generated infrared image. The OHBE utilizes the thermal inertness of radiation layer material to integrate the visible light energy, and generates infrared images with 10-bit grayscale value within 1.25 ms. And the infrared images can be collected in a holding time of 3.75 ms in each refresh cycle. The temperature range of the generated infrared image is 108 K, and the temperature resolution corresponds to a unit grayscale value is 0.1 K. The OHBE proposed has been successfully applied to an infrared target simulator.

MRI image synthesis for fluid-attenuated inversion recovery and diffusion-weighted images with deep learning.

This study aims to synthesize fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted images (DWI) with a deep conditional adversarial network from T1- and T2-weighted magnetic resonance imaging (MRI) images. A total of 1980 images of 102 patients were split into two datasets: 1470 (68 patients) in a training set and 510 (34 patients) in a test set. The prediction framework was based on a convolutional neural network with a generator and discriminator. T1-weighted, T2-weighted, and composite images were used as inputs. The digital imaging and communications in medicine (DICOM) images were converted to 8-bit red-green-blue images. The red and blue channels of the composite images were assigned to 8-bit grayscale pixel values in T1-weighted images, and the green channel was assigned to those in T2-weighted images. The prediction FLAIR and DWI images were of the same objects as the inputs. For the results, the prediction model with composite MRI input images in the DWI image showed the smallest relative mean absolute error (rMAE) and largest mutual information (MI), and that in the FLAIR image showed the largest relative mean-square error (rMSE), relative root-mean-square error (rRMSE), and peak signal-to-noise ratio (PSNR). For the FLAIR image, the prediction model with the T2-weighted MRI input images generated more accurate synthesis results than that with the T1-weighted inputs. The proposed image synthesis framework can improve the versatility and quality of multi-contrast MRI without extra scans. The composite input MRI image contributes to synthesizing the multi-contrast MRI image efficiently.

Highlights from the Detroit SID Vehicle Display Symposium and Exposition

Highlights from the Detroit SID Vehicle Display Symposium and Exposition

A pseudo‐colour enhancement algorithm for high‐bit RAW greyscale image of X‐ray film displaying on low‐bit monitors

X-ray flaw detection is widely used in non-destructive area. The intuitive defect information can be obtained through the X-ray film, which is usually digitized into high greyscale image by a 12-bit or 16-bit, called super 8-bit, industrial scanner. When an ordinary 8-bit monitor displays a super 8-bit greyscale image, it appears loss of detail information, blurring of the image appears and other problems. Therefore, in this paper, a pseudo-colour enhancement algorithm for displaying high-bit RAW images on low-bit monitor was proposed according to the chromatographic mapping relationship based on the visual characteristics of human eye. First, a high grey-scale pseudo-colour enhancement algorithm, called HOTM-HGL, based on hot metal coding was proposed based on the standard film, whose enhancement effect is better than current mainstream algorithms. Second, aiming at the non-standard film, a new stretching function called RAW-Optical-Stretching was reconstructed to improve HOTM-HGL algorithm, called HOTM-HGLS algorithm, whose display effect on ordinary monitors was improved in further. Finally, HOTM-HGLS algorithm was applied in the detection of X-ray film defect, which was convenient for the capture of defect information in the weld. Compared with the existing algorithms, various indicators have been greatly improved, enriching the amount of information and strengthening the image recognition effects.

Auto Segmentation of Lymph Node Microscopy Images

The manual histology assessment on the biopsy tissue sample still remains the gold standard procedure for cancer and its progression in human body. Auto nuclei segmentation is an important method to measure cellularity but often suffered an issue due to the present of overlapping nuclei. The implementation of auto segmentation of cells could speed up the process of histology assessment for cancer cases. The first step to implement, a wide data profile of normal and cancerous need to be compile and analyze further as a reference guide. Tissue data profile can be collected based on cellularity property of the tissue which can be automatically segmented using MATLAB software. The objective of the study is to develop an auto nuclei segmentation using MATLAB software to measure cellularity between normal and cancerous cells of lymph node tissue. Histological images of the tissue were analyzed using MATLAB software by using thresholding method and the result was compared with ImageJ. The pre-processing part of the image processing incudes converting the image into 8-bit grayscale image. The segmentation parts include adaptive filtering to remove the noise using Wiener filter and the thresholding Otsu method. Results from the ImajeJ and manual counting on the cellularity shows a comparable results to the automated cellularity measured using MATLAB. The cellularity of the cancerous lymph nodes was found lower than normal lymph nodes.

U-Net architecture variants for brain tumor segmentation of histogram corrected images

Abstract In this paper we propose to create an end-to-end brain tumor segmentation system that applies three variants of the well-known U-Net convolutional neural networks. In our results we obtain and analyse the detection performances of U-Net, VGG16-UNet and ResNet-UNet on the BraTS2020 training dataset. Further, we inspect the behavior of the ensemble model obtained as the weighted response of the three CNN models. We introduce essential preprocessing and post-processing steps so as to improve the detection performances. The original images were corrected and the different intensity ranges were transformed into the 8-bit grayscale domain to uniformize the tissue intensities, while preserving the original histogram shapes. For post-processing we apply region connectedness onto the whole tumor and conversion of background pixels into necrosis inside the whole tumor. As a result, we present the Dice scores of our system obtained for WT (whole tumor), TC (tumor core) and ET (enhanced tumor) on the BraTS2020 training dataset.

Tensile and microstructural properties of unidirectional coir bio-derived epoxy composites

The study investigates the possibilities of reinforcing bio-derived epoxy (bio-epoxy) polymer with unidirectional arrays of coir fibre using hand layup. The coir fibres were unidirectionally prepared in two layers. The tensile properties such as strength, Young’s modulus and elongation at break were found to be 43.83 MPa, 2.4 GPa and 2.72 % respectively. The tensile strength of coir/bio-epoxy composite was higher than the unreinforced bio-epoxy resin. The fibre volume fraction of the composites obtained using ImageJ on an 8-bit grey scale was 34%. The optical microstructure of the composites shows the distribution of the fibres within the bio-epoxy matrix.

High speed fringe projection for dynamic shape measurement using binary phase mask. Part 1: theory and simulation

Projection rates of up to 30,000 greyscale fringe patterns per second have been achieved recently by defocusing binary fringe patterns from a digital micromirror device (DMD) based projector. Part 1 of this two-part paper describes the design of a binary phase mask, based on a virtual scatter plate, for the purpose of enhancing the performance of a binary fringe projector. The phase mask's anisotropic point spread function (PSF) produces a well-defined blur of the fringes parallel to the fringe direction, thereby minimising degradation of fringe contrast. The shape of the PSF is also shown, by means of a polychromatic Fourier optics model, to be insensitive to projection distance over a range of ±10% of the standoff distance. Two new binary fringe design methods are proposed, including extensions to optimize the system performance in the case of a mismatch between camera and projector framing rates. Expressions for the phase noise are derived as a function of the phase mask design parameters, which demonstrate that fringe quality comparable to traditional 8-bit greyscale fringes is achievable at projection rates over two orders of magnitude higher.

A Simple and Precise Estimation of Water Sliding Angle by Monitoring Image Brightness: A Case Study of the Fluid Repellency of Commercial Face Masks

Fluid repellency of a hydrophobic surface has been typically demonstrated in terms of water sliding angle. A drop shape analysis method with a written computer algorithm monitoring the image brightness was proposed to precisely estimate the sliding angle. A hydrophobic surface coated with silanized silicon dioxide or polytetrafluoroethylene was selected as a known sample for the method validation. Average pixel brightness in an 8-bit grayscale unit rapidly increased after a water drop rolled off the surface, thus removing its black pixels. The resulting sliding angle was then determined as the tilt angle of the sample stage related to the sliding time at the brightness leap. The optimized angular speed of the rotor at 0.1 degrees per frame was chosen to avoid an overestimation of the sliding angle due to the deceleration. The proposed method yielded accurate sliding angles with an error of less than 0.2 degrees. It was then applied to study the fluid resistance of commercial face masks including disposable surgical masks and reusable fabric masks. It was found that the outermost layer of the single-use surgical masks can moderately repel a water drop with a sliding angle of 49.4 degrees. Meanwhile, the pre-coated fabric masks retained high protection efficiency at a sliding angle of less than 45 degrees after about 20 wash cycles. In addition, a raw muslin fabric coated with a commercial water-repellent spray could be a promising and affordable alternative to the surgical mask during the pandemic with high water repellency even after a few washes. The results suggested that, besides the hydrophobicity indicated by the typical contact angle, the precise sliding angle estimated by the proposed alternative method could additionally provide crucial information that might lead to a detailed discussion of the fluid repellency of rough materials.

High speed fringe projection for dynamic shape measurement using binary phase mask. Part 2: manufacture and test

Dynamic measurement of object shape is now achievable at projection rates of up to 30,000 binary fringe patterns per second from a digital micromirror device (DMD) based projector. This two-part paper describes the design, manufacture and test of a binary phase mask in the projection system that produces high-quality greyscale fringes from the binary patterns, with much reduced phase noise compared to the projector defocus approach that has been used until now. Part 2 describes the experimental verification and characterization of the phase masks, manufactured using photolithography and dry etching from the design methods described in Part 1. The height distribution of two masks with point spread function (PSF) dimensions of 1 × 256 and 4 × 64 pixels were assessed using coherence scanning interferometry and contact surface profilometry. Phase noise was determined using standard temporal unwrapping fringe sequences and found to be 20–50% higher than a traditional 8-bit greyscale approach. The projector lens distortion has been observed, and the corresponding compensation method shown to significantly improve the quality of the projected fringes. Increasing the number of projector frames per camera frame reduced phase noise, to less than one-half the 8-bit values for a 10-slice sequence. Fringe image acquisition rates for the 1-slice and 10-slice sequences are up to 255 × and 25 × faster than for the 8-bit greyscale sequence, respectively. Finally, examples are presented of fringe patterns and wrapped phase maps from a high-speed system used to measure moving objects, with projection and acquisition rates of up to 9515 frames s−1.

Two-in-One Secret Image Sharing Scheme with Higher Visual Quality of the Previewed Image

Secret image sharing (SIS) scheme is a secret image encoding and decoding scheme that reconstructs the secret image only if the number of participants is sufficient. In contrast, inadequate participants gain no information about the secret image. Two-in-one secret image sharing (TiOSIS) scheme is a kind of SIS scheme with two decoding options, quick preview without computation and accurate recovery with computer. For higher decoding speed, Li et al. proposed an improved two-in-one secret image sharing scheme, utilizing Boolean operation for less computational complexity, where the visual quality of the previewed image is deteriorated. In this paper, we use q-bit gray visual cryptography to build a mathematical model for better visual quality of the previewed image based on Li et al.’s TiOSIS scheme. The black sub-pixels of shadows corresponding to a black secret pixel are replaced by a q-bit grayscale value rather than an 8-bit grayscale value where q is a positive integer smaller than 8. The theoretical analysis and experiments are exhibited to guarantee feasibility and effectiveness of the proposed scheme.

Evaluation of peripapillary vascular flow in patients with Thyroid-Associated Ophthalmopathy (TAO) by OCT Angiography

PurposeTo evaluate changes in peripapillary vascular blood flow indices (PVBFI) in patients with thyroid-associated ophthalmopathy (TAO) using OCT angiography (OCTA) technology.MethodsPatients with TAO and control subjects matched for age and sex were included in the study. Eye examination, Clinical Activity Score (CAS) evaluation and OCTA scan analysis (Topcon ImageNet 6; DRI OCT Triton, Topcon Corporation) were performed. In particular, PVBFI of the superficial capillary plexus (SCP), deep capillary plexus (DCP), outer retina (OR) and choriocapillaris (CC) layers were obtained by OCTA and extracted from 8-bit greyscale OCT images using the ImageJ software package.ResultsTwenty-six patients with TAO (19 females, mean age 54.7 ± 5.2 and 7 males, mean age 51.4 ± 16.3) were compared with 26 healthy subjects (15 females, mean age 48.2 ± 14.1 and 11 males, mean age 53.1 ± 15.2). Both DCP-PVBF and CC-PVBFI were significantly reduced in TAO patients compared to control eyes (28.6 ± 2.1 vs. 29.7 ± 0.93, p = 0.002; 46.5 ± 1.72 vs. 47.2 ± 1.2, p = 0.019 respectively); on the other hand, no statistically significant differences were found in SCP-PVBFI and OR-PVBFI in TAO patients compared to healthy subjects (p > 0.05). Also, CC-PVBFI was associated with elevated values of CAS (p = 0.018) and ROC curve showed that patients with elevated CC-PVBFI were correlated with active TAO (CAS > 3) (p = 0.012).ConclusionsTAO disease may be associated with changes in DCP-PVBFI and CC-PVBFI; also, CC-PVBFI seems to correlate with disease activity.

Investigation on operation robustness of p-type low-temperature polycrystalline silicon thin-film transistor-based micro light-emitting diode pixel circuit using pulse width modulation under component fluctuation

In this study, we have investigated the operation robustness of a p-type low-temperature polycrystalline silicon (LTPS) thin-film transistor (TFT)-based micro light-emitting diode (µLED) pixel circuit adopting pulse width modulation (PWM) under circuit component fluctuations. The wavelength shift of µLEDs, depending on the current density, was suppressed by implementing PWM. The PWM pixel circuit controlled the emission time with constant µLED current in the simulated and measured results. In addition, the wavelength shift was suppressed below 0.48% within the 10-bit grayscale range. Furthermore, the component tolerance of the pixel circuit was investigated by simulating the error rate of µLED emission time with varying threshold voltage, mobility, subthreshold swing, and capacitance. The pixel circuit exhibited a robust operation with a maximum error rate of 4.0% under a component fluctuation of ±10%. Consequently, the µLED pixel circuit adopting PWM suppressed the wavelength shift of µLEDs and demonstrated robust circuit operation under component fluctuation.