Subjective Quality Assessment Research Articles

Evaluation the effect of wide-body detector CT under free breathing combined with cardiac motion correction technology on CCTA image quality

PurposeTo explore the feasibility of using wide-body detector Computed Tomography (CT) combined with Cardiac Motion Correction (CMC) technology for coronary Computed Tomography angiography (CCTA) in free breathing state and its impact on image quality. Methods120 patients who underwent CCTA scans at our institution from March 2023 to December 2023 were collected in this retrospective study. Recorded the coronary artery images before applying CMC technology as the control group, and the images after applying CMC technology as the experimental group. Patients were divided into two groups by different heart rate (HR), Group A (HR > 70 bpm) and Group B (HR ≤ 70 bpm), with 66 patients in group A and 54 patients in group B. Subjective image quality assessments were performed on the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) proximal segments. These assessments were conducted by two senior radiologists using a double-blind approach and a 4-point scale (1 indicating poor image quality and 4 indicating excellent image quality). The subjective scores among the three coronary artery segments were analyzed by chi-square test, using Kappa coefficient to analyze the inter-observer agreement. ResultsThe control group had a subjective score of 3.37 ± 0.81/3.27 ± 0.83 for the LCX, 2.97 ± 0.85/2.93 ± 0.78 for the LAD, and 2.70 ± 0.75/2.80 ± 0.66 for the RCA. The experimental group had a subjective score of 3.90 ± 0.31/3.83 ± 0.38 for the LCX, 3.83 ± 0.38/3.87 ± 0.35 for the LAD, and 3.87 ± 0.35/3.83 ± 0.38 for the RCA. There was a great enhancement in the image quality observed in the experimental group when contrasted with the control group both in group A and group B (all P < 0.05). The inter-observer consistency of LCX, LAD and RCA were 0.726, 0.801 and 0.734 in control group and 0.769, 0.870 and 0.870 in experimental group. ConclusionThe utilization of CMC technology significantly enhances the quality of CCTA images acquired during free breathing.

Value of vendor-agnostic deep learning image denoising in brain computed tomography: A multi-scanner study.

To evaluate the effect of a vendor-agnostic deep learning denoising (DLD) algorithm on diagnostic image quality of non-contrast cranial computed tomography (ncCT) across five CT scanners.This retrospective single-center study included ncCT data of 150 consecutive patients (30 for each of the five scanners) who had undergone routine imaging after minor head trauma. The images were reconstructed using filtered back projection (FBP) and a vendor-agnostic DLD method. Using a 4-point Likert scale, three readers performed a subjective evaluation assessing the following quality criteria: overall diagnostic image quality, image noise, gray matter-white matter differentiation (GM-WM), artifacts, sharpness, and diagnostic confidence. Objective analysis included evaluation of noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and an artifact index for the posterior fossa.In subjective image quality assessment, DLD showed constantly superior results compared to FBP in all categories and for all scanners (p<0.05) across all readers. The objective image quality analysis showed significant improvement in noise, SNR, and CNR as well as for the artifact index using DLD for all scanners (p<0.001).The vendor-agnostic deep learning denoising algorithm provided significantly superior results in the subjective as well as in the objective analysis of ncCT images of patients with minor head trauma concerning all parameters compared to the FBP reconstruction. This effect has been observed in all five included scanners. · Significant improvement of image quality for 5 scanners due to the vendor-agnostic DLD. · Subjects were patients with routine imaging after minor head trauma. · Reduction of artifacts in the posterior fossa due to the DLD. · Access to improved image quality even for older scanners from different vendors. · Kapper C, Müller L, Kronfeld A et al. Value of vendor-agnostic deep learning image denoising in brain computed tomography: A multi-scanner study. Fortschr Röntgenstr 2024; DOI 10.1055/a-2290-4781.

Yoga Exercises as a Therapeutic Approach for Adults with Insomnia to Promote better Sleep: A Randomized Control Trial

Background: Insomnia is a prevalent sleep disorder that significantly impacts the quality of life and is associated with various health complications, including high blood pressure, heart disease, diabetes, anxiety, and depression. Traditional treatments for insomnia often involve pharmacological interventions, but there is growing interest in alternative therapies such as yoga. This study investigates the efficacy of yoga as a therapeutic approach to improving sleep quality in adults with insomnia. Objective: The objective of this study was to evaluate the effects of a structured yoga program on sleep quality and sleep latency in adults diagnosed with insomnia. Methods: The study employed a cross-sectional design conducted at multiple healthcare facilities, including the Physiotherapy Outpatient Department at Holy Family Hospital, Benazir Bhutto Hospital, and District Headquarters Hospital in Rawalpindi. The study duration was four months, involving 54 participants selected through random sampling techniques. Inclusion criteria included adults aged 18 to 65 years diagnosed with insomnia according to the International Classification of Sleep Disorders (ICSD) or the Diagnostic and Statistical Manual of Mental Disorders (DSM). Exclusion criteria included severe medical or psychiatric disorders, substance abuse, pregnancy, or recent changes in sleep medication. Participants in the intervention group engaged in a standardized yoga program consisting of gentle yoga postures, controlled breathing techniques, and mindfulness meditation, conducted twice weekly for eight weeks, with each session lasting 60 minutes. The control group received standard care for insomnia. Data collection involved subjective assessments of sleep quality using validated questionnaires and objective measures through polysomnography. Statistical analysis was performed using SPSS version 25.0, with independent sample t-tests comparing means between groups and repeated measures ANOVA for within-group analysis. Results: The yoga group showed significant improvements in subjective sleep quality and sleep latency. The mean sleep quality score improved from 2.18 ± 0.66 pre-intervention to 0.92 ± 0.37 post-intervention (p=0.0001), while the control group showed a less marked improvement from 2.37 ± 0.48 to 2.03 ± 0.18 (p=0.0012). Sleep latency in the yoga group decreased from 3.00 ± 0.00 to 1.29 ± 0.40 (p=0.0002), whereas the control group showed a reduction from 2.44 ± 0.49 to 2.11 ± 0.31 (p=0.0013). ANOVA results confirmed the statistical significance of these findings, with an F-value of 69.897 for sleep quality (p=0.0001) and 361.947 for sleep latency (p=0.0002). Conclusion: The findings indicate that a structured yoga program significantly improves sleep quality and reduces sleep latency in adults with insomnia. Yoga appears to be an effective non-pharmacological intervention for managing insomnia, offering a viable alternative to traditional treatments.

Review of Image Quality Assessment Methods for Compressed Images.

The compression of images for efficient storage and transmission is crucial in handling large data volumes. Lossy image compression reduces storage needs but introduces perceptible distortions affected by content, compression levels, and display environments. Each compression method generates specific visual anomalies like blocking, blurring, or color shifts. Standardizing efficient lossy compression necessitates evaluating perceptual quality. Objective measurements offer speed and cost efficiency, while subjective assessments, despite their cost and time implications, remain the gold standard. This paper delves into essential research queries to achieve visually lossless images. The paper describes the influence of compression on image quality, appropriate objective image quality metrics (IQMs), and the effectiveness of subjective assessment methods. It also provides an overview of the existing literature, surveys, and subjective and objective image quality assessment (IQA) methods. Our aim is to offer insights, identify challenges in existing methodologies, and assist researchers in selecting the most effective assessment approach for their needs.

HDRC: a subjective quality assessment database for compressed high dynamic range image

AbstractEvaluating the quality of high dynamic range (HDR) images has emerged as a challenging and contemporary topic with the proliferation of HDR content. In this work, a new HDR compression (HDRC) database is proposed, aiming to provide a benchmark for the development of full-reference HDR image quality assessment (IQA) algorithms when facing the latest HDR compression distortions. In particular, the proposed HDRC database is the first HDR-IQA database to incorporate Versatile Video Coding (VVC) compression distortions, closely associated with practical application scenarios. Furthermore, the proposed HDRC database is currently the largest HDR-IQA database, including 80 reference images and 400 distorted images. Extensive experiments are conducted by studying the performance compared to existing HDR-IQA databases when evaluating three HDR-specific IQA models and nine IQA models prevalent for low dynamic range (LDR) content, revealing the challenges the proposed HDRC database brings. The results indicate that the existing IQA models demonstrate noticeable decreases in accuracy when assessing new compression distortions, underscoring the need for the development of novel HDR-IQA models. Consequently, the suggested HDRC database can serve as a potential database for HDR-IQA research, fostering a comprehensive exploration of the associated fields.

Feasibility of Weight-based Tube Voltage and Iodine Delivery Rate for Coronary Artery CT Angiography.

The objective of this study was to evaluate the feasibility of weight-based tube voltage and iodine delivery rate (IDR) for coronary artery CT angiography (CCTA). A total of 193 patients (mean age: 58 ± 12 years) with suspected coronary heart disease indicated for CCTA between May and October 2022 were prospectively enrolled. The subjects were divided into five groups according to body weight: < 60 kg, 60 - 69 kg, 70 - 79 kg, 80 - 89 kg, and ≥ 90 kg. The tube voltage and IDR settings of each group were as follows: 70 kVp/0.8 gI/s, 80 kVp/1.0 gI/s, 80 kVp/1.1 gI/s, 100 kVp/1.5 gI/s, and 100 kVp/1.5 gI/s, respectively. Objective image quality data included the CT value and standard deviation (noise) of the aortic root (AR), the proximal left anterior descending branch (LAD), and the distal right coronary artery (RCA), as well as the signal-to-noise ratio and contrast-to-noise ratio of the LAD and RCA. Subjective image quality assessment was performed based on the 18-segment model. Contrast and radiation doses, as well as effective dose (ED), were recorded. All continuous variables were compared using either the one-way ANOVA or the Kruskal-Wallis rank sum test. No significant differences were observed in all objective and subjective parameters of image quality between the groups (P > 0.05). However, significant differences in contrast and radiation doses were observed (P < 0.05). The contrast doses across the weight groups were 27 mL, 35 mL, 38 mL, 53 mL, and 53 mL, respectively, while the ED were 1.567 (1.30, 2.197) mSv, 1.53 (1.373, 1.78) mSv, 2.113 (1.963, 2.256) mSv, 4.22 (3.771, 4.483) mSv, and 4.786 (4.339, 5.536) mSv, respectively. Weight-based tube voltage and IDR yielded consistently high image quality, and allowed for further reduction in contrast and radiation exposure during CCTA for coronary artery diseases.

PCQD‐AR: Subjective quality assessment of compressed point clouds with head‐mounted augmented reality

AbstractThis letter fully studies the coloured point cloud quality assessment in augmented reality (AR) environment through subjective test. Firstly, a point cloud dataset, named point cloud quality dataset‐AR, including ten reference point clouds and their 90 distorted versions is presented, which were generated using the reference software of video‐based point cloud compression across various combinations of geometry and texture quantization parameters. Then, the impact of geometry and texture distortions on perceived quality of point clouds in AR environment was discussed in detail. Moreover, the performance of existing objective point cloud quality assessment metrics on the proposed dataset is evaluated. The subjective dataset including the values of mean opinion score were released to public.

الاقتراب من الزمن الحقيقي لتكوين الصور المتكاملة ثلاثية الابعاد

Generating a truly photo-realistic 3D real-time view capability in an ergonomic and cost effective manner is a crucial engineering challenge. In this paper, the advanced integral imaging methodology is proposed that is based on microlens arrays to generate 3D Holoscopic images by the intersection ray bundle that defines each image point in the associated scene at the correct spatial place. The core idea of the novel algorithm reported in this paper is to accelerate the computer generation of photo-realistic still 3D Holoscopic images based on multiprocessor ray-traced system. Consequently a significantly reduce in running time is successfully completed. Multiple subjective and objective images quality assessments are addressed and as a result there was not any observable distortion in images quality. The results obtained are very satisfactory and for the first time that the new hybrid algorithm has achieved the saving in terms of execution rendering time approximately (60 % - 78 %) that a near to real-time computer generation of 3D Holoscopic images. Keywords: Real-time Computer Generation content of 3D Holoscopic Images, Interpolation 3D integral images, Computer Graphics, Spatial Coherence, Ray Tracing, 3DTV.

Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester

BackgroundThis study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists.Materials and methodsThis prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments.ResultsThere were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively.ConclusionsCUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.

A machine learning-based assessment of subjective quality of life

A machine learning-based assessment of subjective quality of life

Autoencoder based image quality metric for modelling semantic noise in semantic communications

AbstractSemantic communication has attracted significant attention as a key technology for emerging 6G communications. This paper proposes an autoencoder based image quality metric to quantify the semantic noise. An autoencoder is initially trained with the reference image to generate the encoder‐decoder model and calculate its Latent Vector Space (LVS) and then a semantically generated/received image is inserted into the same autoencoder to create the corresponding LVS. Finally, both LVS are used to define the Euclidean space to calculate the mean square error between two LVS. Results indicate that the proposed model has a high correlation coefficient of 88% with subjective quality assessment and commonly used conventional metrics completely failed in semantic noise modelling.

P422 Prevalence of poor sleep quality assessed by wrist actigraphy and sleep questionnaire in Inflammatory Bowel Disease patients and its association with disease activity and quality of life

Abstract Background An association between active inflammatory bowel disease (IBD) and poor sleep quality has been proposed, however studies evaluating both subjective and objective assessment of disease activity and sleep quality are limited. Our study aimed to investigate the prevalence of poor sleep quality assessed by wrist actigraphy and sleep questionnaires in IBD patients and its association with disease activity and quality of life. Methods A prospective observational study was conducted in Siriraj Hospital, Mahidol University, Bangkok, Thailand from March 2021 to December 2022. Eligible IBD patients were categorized into remission, mild, and moderate-to-severe groups, based on standard clinical disease activity scores. Demographic data, inflammatory markers, inflammatory bowel disease questionnaire (IBDQ), sleep questionnaire (Pittsburgh Sleep Quality Index, PSQI), and seven-day sleep data from wrist actigraphy (Actiwatch®, CamNtech, Cambridge, United Kingdom) were obtained. The prevalence of sleep disorder and group comparison were analyzed. Results Eighty-four participants (40 Crohn’s disease, 44 UC), consisting of 60 remission, 16 mild, and 8 moderate-to-severe disease activity, were enrolled. Baseline demographic data were comparable between each group. Lower hemoglobin and albumin levels, and higher serum C-reactive protein, and fecal calprotectin levels were found in the more clinically active groups (table1). Fifty patients (60%) had poor sleep defined by PSQI &amp;gt; 5 with a trend to be higher in the group with active symptoms (57% in remission, 63% in mild, and 75% in moderate-to-severe group, p=0.31). Using actigraphy, the group with moderate-to-severe symptoms tended to have longer sleep latency, more frequently awake after sleep, and poorer sleep efficiency than the other groups (Figure 1). Patients with more severe disease activity had poorer quality of life with a mean IBDQ of 190 in remission, 159 in mild, and 134 in moderate-to-severe group (p&amp;lt;0.001). Conclusion Poor sleep quality is common among IBD patients, even those with clinical remission. Those with more severe symptoms had poorer sleep quality and worse quality of life. Sleep assessment and treatment should be integrated into IBD standard clinical care.

Astigmatism Influences Quantitative and Qualitative Analysis in Optical Coherence Tomography Angiography Imaging.

The purpose of this paper was to study the influence of astigmatism in optical coherence tomography angiography (OCTA) images in a quantitative and qualitative analysis. This was a prospective, cross-sectional study. We included 110 eyes of 110 patients: 20 eyes without astigmatism and 90 eyes with astigmatism ≥0.5 diopters (D). We performed a macula centered OCTA as a reference image. In patients without astigmatism, registered follow-up scans were performed after induction of -1 and -2 D astigmatism. In patients with astigmatism, we performed the follow-up scan after astigmatism correction. We used a set of cylindrical lenses attached to the camera head of the SPECTRALIS (Heidelberg Engineering, Heidelberg, Germany). A quantitative and qualitative analysis of the superficial vascular complex (SVC) and deep vascular complex (DVC) was performed. The main outcome measures were vessel density (VD), image quality, and the presence of artifacts. Mean VD of the SVC was significantly higher in the reference images compared with the images after induction of -2 D. Differences with -1 D were nonsignificant. Higher degrees of astigmatisms had higher VD dropout (0.012-0.02 per diopter in SVC). Astigmatism axis showed no relevance in our cohort. Image quality assessed by two independent observers was graded as higher in images without astigmatism. Defocus and attenuation were more prevalent in images with astigmatism. Astigmatism of -2 D affects quantification of VD in OCTA images, mainly affecting the SVC, as well as the subjective quality assessment. Correction of this refractive error might be necessary for an accurate quantitative assessment of OCTA images. Correcting astigmatism of 2 D or greater appears to be necessary when analyzing OCTA images.

Customer Product Choice: The Effect of Product Quality on Relative price and Price fairness and their implication on Customer Product Choice

This study examines the influence of product quality on individuals' perceptions of relative prices and price justice, as well as the potential consequences for consumer decision-making in product selection. This study employs robust statistical analysis to get insights into customers' decision-making processes when purchasing products and selecting brands, particularly about product attributes and pricing. The study employed a non-parametric Structural Equation Modeling PLS technique, which involved a sample of 100 consumers who had previously consumed cigarette goods in the urban area of Bandung. The questionnaire was distributed through social media platforms, utilizing a Google Form link. The employed sample method is convenience sampling, wherein clients are requested to complete a structured questionnaire that has been supplied. The poll encompassed inquiries about participants' perceptions regarding the quality of the product, its comparable pricing, and the appropriateness of the price. The survey data were subjected to rigorous statistical analysis, encompassing several analytical techniques such as regression analysis and hypothesis testing. The study's findings indicate that a product's quality plays a substantial role in shaping consumers' evaluations of comparable prices and perceptions of price justice. Consumers tend to make product selections predicated upon their subjective quality assessment, shaping their perception of the product's price. The presence of excellent product quality can mitigate price barriers, as customers exhibit a greater propensity to pay elevated costs for things they believe to possess superior quality. Furthermore, this study demonstrates that comparable costs and the perception of price justice influence consumer product choices. This condition highlights the significance of prudent pricing within a company's marketing strategy, whereby competitive and equitable pricing can catalyze consumers to opt for specific products. However, a further noteworthy discovery is that the relative pricing and price reasonableness factors do not influence customers' brand preferences. This condition suggests that when considering the choice of a brand, several elements, such as brand image, individual preferences, or distinctive brand characteristics, may exert a more significant impact. The correlation between product and brand compatibility plays a significant part in consumers' decision-making process when it comes to selecting a brand. The findings of this study offer significant implications for businesses in enhancing their marketing and pricing strategies. Furthermore, they contribute to a more comprehensive comprehension of consumer decision-making processes within the product and brand choices framework. In order to achieve success in a competitive and dynamic business climate, it is imperative to possess a comprehensive comprehension of the various elements that impact consumer decision-making.

DashReStreamer: Framework for Creation of Impaired Video Clips under Realistic Network Conditions

The continuous rise of multimedia entertainment has led to an increased demand for delivering outstanding user experience of multimedia content. However, modelling user-perceived Quality of Experience (QoE) is a challenging task, resulting in efforts for better understanding and measurement of user-perceived QoE. To evaluate user QoE, subjective quality assessment, where people watch and grade videos, and objective quality assessment in which videos are graded using one or many objective metrics are conducted. While there is a plethora of video databases available for subjective and objective video quality assessment, these videos are artificially infused with various temporal and spatial impairments. Videos being assessed are artificially distorted with startup delay, bitrate changes, and stalls due to rebuffering events. To conduct a more credible quality assessment, a reproduction of original user experiences while watching different types of streams on different types and quality of networks is needed. To aid current efforts in bridging the gap between the mapping of objective video QoE metrics to user experience, we developed DashReStreamer, an open-source framework for re-creating adaptively streamed video in real networks. The framework takes inputs in the form of video logs captured by the client in a non-regulated setting, along with an.mpd file or a YouTube URL. The ultimate result is a video sequence that encompasses all the data extracted from the video log. DashReStreamer also calculates popular video quality metrics like PSNR, SSIM, MS-SSIM and VMAF. Finally, DashReStreamer allows creating impaired video sequences from the popular streaming platform, YouTube. As a demonstration of framework usage we created a database of 332 realistic video clips, based on video logs collected from real mobile and wireless networks. Every video clip is supplemented with bandwidth trace and video logs used in its creation and also with objective metrics calculation reports. In addition to dataset, we performed subjective evaluation of video content, assessing its effect on overall user QoE. We believe that this dataset and framework will allow the research community to better understand the impacts of video QoE dynamics.

Secondary traumatic stress in working nurses studying part time in a bachelor or Master’s nursing program in Croatia: a cross-sectional study

BackgroundNurses are more likely to be exposed to human suffering than other healthcare professionals. Persons exposed to indirect trauma can experience symptoms of posttraumatic stress disorder, symptoms of avoidance, arousal and intrusion. Secondary traumatic stress (STS) occurs when a person hears about the firsthand traumatic experiences of another. This study aimed to explore the prevalence of STS among working nurses enrolled at a university nursing program.MethodsA cross-sectional study was conducted among nurses working in healthcare enrolled in university bachelor’s or Master’s nursing studies at the Catholic University of Croatia in November 2017. Data were collected using the Secondary Traumatic Stress Scale (STSS) and two items from the World Health Organization quality of life brief version (WHOQOL-BREF).ResultsThe study included 151 students; the response rate was 70%. The mean STS score was 38, indicating that the students on average suffered from moderate STS. Half of participating nurses met the criteria for STS. Working nurses enrolled in Master’s studies had lower STS scores than those enrolled into bachelor studies (t = 4.14, df = 149, p < 0.01). The level of STS had a negative correlation with participants’ quality of life assessment (r=-0.392, p < 0.01) and satisfaction with their health (r=-0.387, p < 0.01). We also found a significant positive correlation between subjective assessment of quality of life and satisfaction with personal health (r = 0.432, p < 0.01). We did not find a significant association between the level of STS and sex (r=-0.094) or years of nursing work experience (r=-0.069). Level of STS varied depending on the participants’ workplace, years of experience in that workplace and their work shifts. The highest levels of STS were seen in nurses working in the internal medicine department, those with 10–14 years of work experience in the current workplace, and those who work block shifts (12-hr shift followed by 24-hour shift).ConclusionOver half of working nurses attending university studies had at least moderate STS. Furthermore, STS was negatively associated with participants’ perception of quality of life and satisfaction with their health. Prevention and alleviation interventions could reduce the burden of STS among nurses.

How subjective CT image quality assessment becomes surprisingly reliable: pairwise comparisons instead of Likert scale.

The aim of this study is to improve the reliability of subjective IQ assessment using a pairwise comparison (PC) method instead of a Likert scale method in abdominal CT scans. Abdominal CT scans (single-center) were retrospectively selected between September 2019 and February 2020 in a prior study. Sample variance in IQ was obtained by adding artificial noise using dedicated reconstruction software, including reconstructions with filtered backprojection and varying iterative reconstruction strengths. Two datasets (each n = 50) were composed with either higher or lower IQ variation with the 25 original scans being part of both datasets. Using in-house developed software, six observers (five radiologists, one resident) rated both datasets via both the PC method (forcing observers to choose preferred scans out of pairs of scans resulting in a ranking) and a 5-point Likert scale. The PC method was optimized using a sorting algorithm to minimize necessary comparisons. The inter- and intraobserver agreements were assessed for both methods with the intraclass correlation coefficient (ICC). Twenty-five patients (mean age 61 years ± 15.5; 56% men) were evaluated. The ICC for interobserver agreement for the high-variation dataset increased from 0.665 (95%CI 0.396-0.814) to 0.785 (95%CI 0.676-0.867) when the PC method was used instead of a Likert scale. For the low-variation dataset, the ICC increased from 0.276 (95%CI 0.034-0.500) to 0.562 (95%CI 0.337-0.729). Intraobserver agreement increased for four out of six observers. The PC method is more reliable for subjective IQ assessment indicated by improved inter- and intraobserver agreement. This study shows that the pairwise comparison method is a more reliable method for subjective image quality assessment. Improved reliability is of key importance for optimization studies, validation of automatic image quality assessment algorithms, and training of AI algorithms. • Subjective assessment of diagnostic image quality via Likert scale has limited reliability. • A pairwise comparison method improves the inter- and intraobserver agreement. • The pairwise comparison method is more reliable for CT optimization studies.

Sleep quality and its associated factors among postoperative patients: A cross-sectional study

Sleep is very important and necessary for human health. For patients undergoing surgery, they should have good sleep to restore both physiological and psychological health. This has a positive impact on the process of recovering damaged tissues, helping to heal wounds earlier, preventing complications, shortening the length of hospital stay, and reducing treatment costs. Objectives: This study was conducted to examine the quality of sleep and identify associated factors in patients who underwent surgery at the General Surgical Ward, Tay Nguyen Regional General Hospital. Research subjects and methods: A cross-sectional descriptive study was performed on 374 postoperative patients who met the sampling criteria and randomization. Data was collected through the interview technique using a structured questionnaire. Sleep quality was assessed by the Pittburgh Sleep Quality Index instrument. Results: 78.1% postoperative patients had poor sleep quality with mean score of PSQI scale was 10.3 (range: 0-21; SD= 3.27). Most of the patients had a subjective assessment of sleep quality at fairly bad (27.8%) and very bad (41.7%). Age group is one of the non-environmental factors associated with sleep quality in this population. Environmental factors, including lighting in the patient's room, activities of medical staff, and noise from equipment, are associated with the patient's sleep quality (p &lt; 0.05).

A Study of Subjective and Objective Quality Assessment of HDR Videos.

As compared to standard dynamic range (SDR) videos, high dynamic range (HDR) content is able to represent and display much wider and more accurate ranges of brightness and color, leading to more engaging and enjoyable visual experiences. HDR also implies increases in data volume, further challenging existing limits on bandwidth consumption and on the quality of delivered content. Perceptual quality models are used to monitor and control the compression of streamed SDR content. A similar strategy should be useful for HDR content, yet there has been limited work on building HDR video quality assessment (VQA) algorithms. One reason for this is a scarcity of high-quality HDR VQA databases representative of contemporary HDR standards. Towards filling this gap, we created the first publicly available HDR VQA database dedicated to HDR10 videos, called the Laboratory for Image and Video Engineering (LIVE) HDR Database. It comprises 310 videos from 31 distinct source sequences processed by ten different compression and resolution combinations, simulating bitrate ladders used by the streaming industry. We used this data to conduct a subjective quality study, gathering more than 20,000 human quality judgments under two different illumination conditions. To demonstrate the usefulness of this new psychometric data resource, we also designed a new framework for creating HDR quality sensitive features, using a nonlinear transform to emphasize distortions occurring in spatial portions of videos that are enhanced by HDR, e.g., having darker blacks and brighter whites. We apply this new method, which we call HDRMAX, to modify the widely-deployed Video Multimethod Assessment Fusion (VMAF) model. We show that VMAF+HDRMAX provides significantly elevated performance on both HDR and SDR videos, exceeding prior state-of-the-art model performance. The database is now accessible at: https://live.ece.utexas.edu/research/LIVEHDR/LIVEHDR_index.html. The model will be made available at a later date at: https://live.ece.utexas.edu//research/Quality/index_algorithms.htm.

MsgFusion: Medical Semantic Guided Two-Branch Network for Multimodal Brain Image Fusion

Multimodal image fusion plays an essential role in medical image analysis and application, where computed tomography (CT), magnetic resonance (MR), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) are commonly-used modalities, especially for brain disease diagnoses. Most existing fusion methods do not consider the characteristics of medical images, and they adopt similar strategies and assessment standards to natural image fusion. While distinctive medical semantic information (MS-Info) is hidden in different modalities, the ultimate clinical assessment of the fusion results is ignored. Our MsgFusion first builds a relationship between the key MS-Info of the MR/CT/PET/SPECT images and image features to guide the CNN feature extractions using two branches and the design of the image fusion framework. For MR images, we combine the spatial domain feature and frequency domain feature (SF) to develop one branch. For PET/SPECT/CT images, we integrate the gray color space feature and adapt the HSV color space feature (GV) to develop another branch. A classification-based hierarchical fusion strategy is also proposed to reconstruct the fusion images to persist and enhance the salient MS-Info reflecting anatomical structure and functional metabolism. Fusion experiments are carried out on many pairs of MR-PET/SPECT and MR-CT images. According to seven classical objective quality assessments and one new subjective clinical quality assessment from 30 clinical doctors, the fusion results of the proposed MsgFusion are superior to those of the existing representative methods.