Objective Quality Criteria Research Articles

Towards a taxonomy for business capabilities determining data value

AbstractData and its valuation have gained vital significance in academia and enterprises, coinciding with diverse data valuation approaches encompassing various layers, dimensions, and characteristics. This paper assesses data value determination through a business capability lens based on the TOGAF standard. The paper encompasses (a) constructing a Data Valuation Business Capability (DVBC) taxonomy and (b) validating the taxonomy using two existing data valuation concepts from academia. The methodology involves information systems taxonomy development techniques backed by a previously conducted systematic literature review of 64 articles. The resultant taxonomy comprises four business capability layers, nine dimensions, and 36 characteristics. These layers and dimensions offer business, technology, and organizational perspectives, reflecting the interdisciplinary nature of data valuation alongside an enterprise architecture. Characteristics within these layers and dimensions are either exclusive or non-exclusive based on their contents. The compiled findings meet both objective and subjective quality criteria. The implications of the DVBC are multifaceted, influencing scholars and professionals alike. Scholars gain a cohesive tool enhancing transparency in the extensively debated data value domain, fostering linkages among information systems, enterprise architecture management, and data management. This empowers the progress in developing comprehensive data valuation concepts. Additionally, professionals may employ the DVBC taxonomy as a lighthouse and guiding tool, fostering internal dialog on data valuation. This entails elevating data valuation to a pivotal business capability, necessitating collaborative, regular assessment, and enhancement involving business and technological stakeholders. By adopting this taxonomy, the challenge of consistently determining data value can be effectively addressed in both academia and enterprises.

Noise-optimized virtual monoenergetic reconstructions of dual-energy CT angiographies improve assessability of the lower leg arterial segments in peripheral arterial occlusive disease

IntroductionThe aim of this study was to evaluate the influence of a noise optimized virtual monoenergetic reconstruction algorithm (VMI+) on the image quality and assessability of dual energy (DE) computed tomography angiography (CTA) of the lower extremity runoff. MethodsA total of 118 lower extremity runoff CTA performed on a 3rd generation DE-CT scanner in 109 patients (54 females; 75.6 ± 9.5 years) were included in this retrospective study. Axial image stacks were reconstructed with a standard 120 kV setting and VMI+ of different keV levels. Objective image quality criteria (contrast attenuation, signal-to-noise [SNR] and contrast-to-noise ratio [CNR]) were measured. Two radiologists evaluated subjective image quality regarding intraluminal attenuation and image noise using a 5-point Likert scale. Diagnostic accuracy for significant stenosis (>75%) and vessel occlusion was assessed for 120 kV and 50 keV VMI+ images rated by two radiologists. In all patients, a digital subtraction angiography (DSA) rated by on board-certified radiologist served as the standard of reference. ResultsIntraluminal attenuation was highest in 40/50 keV VMI+ while SNR were similar to 120 kV images. In subjective assessment, intraluminal contrast of 50 keV images was deemed superior compared to 120 kV despite higher image noise. Sensitivity, specificity, and accuracy for detection of a vessel occlusion were similar in 50 keV VMI+ compared to 120 kV (70%/92%/84%; 70%/91%/83%; p < 0.001) but 13 of 118 (11%) lower leg runoffs were only assessable with 50 keV VMI+. ConclusionVMI+ reconstructions improve assessability of DE-CTA by increased luminal attenuation with consistent image noise, also allowing the evaluation of lower leg arterial segments inassessable with standard reconstructions. Implications for practiceProviding higher intraluminal attenuation and similar image noise compared with conventional reconstructions, 50 keV VMI+ may be appropriate for routine evaluation of DE-CTA.

Four decades of developmental dysplastic hip screening according to Graf: What have we learned?

PurposeSonographic hip examination according to Graf is widely accepted standard for diagnosing developmental dysplastic hips (DDH) but it is criticized for alleged intra- and interobserver variations. This review was conducted to evaluate whether objective quality criteria according to the Graf method are fulfilled within scientific literature.MethodsA systematic literature search on Pubmed was performed using the search string: [(DDH) OR (Hip dysplasia)] AND (Graf). Studies suitable by title, abstract, manuscript, containing an image of sonographic hip examination and online accessibility were included into analysis.Results131 studies were included into final analysis. Only 68 (51.9%) presented correct sonographic images according Graf’s criteria. 98 (74.8%) studies plotted alpha-angles (angle between bony roof line and base line) but only 85 (64.8%) studies beta-angles (angle between cartilage roof line and base line). Studies were contributed from 25 countries.ConclusionAssumingly, skepticism regarding the Graf method is based on user errors and insufficient application of the Graf quality assessment algorithm resulting in high intra- and interobserver variations. When performed correctly, the Graf method is of high diagnostic value.

Robust mean shift filter for mixed Gaussian and impulsive noise reduction in color digital images

Noise reduction is one of the most important topics of digital image processing and despite the fact that it has been studied for a long time it remains the subject of active research. In the following work, we present an extension of the Mean Shift technique, which is efficiently reducing the Gaussian noise, so that it is able to cope with the impulsive disturbances. Furthermore, the elaborated technique can be applied to enhance the images corrupted by a mixture of strong Gaussian and impulsive noise, severely decreasing the quality of color digital images. By means of our approach, which is based on a novel similarity measure between a pixel and a patch located in the center of the processing block, even heavily disturbed images can be effectively restored, which enables the success of further stages of the image processing pipeline. We evaluate the efficiency of the proposed method using a publicly available database of test color images and compare the restored images applying a set of standard quality metrics with the results delivered by state-of-the-art denoising methods. Additionally, we compare our method with the Medoid and Quick Shift techniques, accelerating the original Mean Shift algorithm, in terms of objective quality criteria and computational complexity. The results of the performed experiments indicate that the proposed technique is superior to the widely used denoising techniques and can be used as a robust extension of the Mean Shift procedure. In the paper, a particular emphasis is placed on the ability of the presented algorithm to preserve and enhance image edges. The performed experiments evaluated with the use of the Pratt’s index, quantitatively confirm the superiority of the proposed design over the Mean Shift and standard denoising methods. The preservation of edges and even their sharpening is a very important feature of our algorithm whereas the final goal is segmentation, playing a crucial role in various computer vision tasks. The proposed algorithm is intended for the mixed noise reduction in color images, but it can be also applied in multispectral imaging and clustering of multidimensional data. To enable the comparison of our method with the standard denoising techniques and to help applying it in other image processing fields, we made its code freely available.

Despeckling of Ultrasound Images Using Block Matching and SVD in Sparse Representation.

This work proposes a novel scheme for speckle suppression on medical images acquired by ultrasound sensors. The proposed method is based on the block matching procedure by using mutual information as a similarity measure in grouping patches in a clustered area, originating a new despeckling method that integrates the statistical properties of an image and its texture for creating 3D groups in the BM3D scheme. For this purpose, the segmentation of ultrasound images is carried out considering superpixels and a variation of the local binary patterns algorithm to improve the performance of the block matching procedure. The 3D groups are modeled in terms of grouped tensors and despekled with singular value decomposition. Moreover, a variant of the bilateral filter is used as a post-processing step to recover and enhance edges’ quality. Experimental results have demonstrated that the designed framework guarantees a good despeckling performance in ultrasound images according to the objective quality criteria commonly used in literature and via visual perception.

Effectiveness and Feasibility of Internet-Based Interventions for Grief After Bereavement: Systematic Review and Meta-analysis.

BackgroundAlthough grief and its symptoms constitute a normal reaction to experiences of loss, some of those affected still report elevated levels of distress after an extended period, often termed complicated grief. Beneficial treatment effects of face-to-face therapies, for example, grief counseling or cognitive behavioral therapy against complicated grief, have been reported. Evaluations of internet- and mobile-based interventions targeting symptoms of grief in bereaved individuals with regard to objective quality criteria are currently lacking.ObjectiveWe aim to conduct a systematic review and meta-analysis on the effectiveness and feasibility of internet- and mobile-based interventions against symptoms of grief after bereavement.MethodsWe conducted systematic literature searches of randomized controlled trials or feasibility studies published before January 9, 2020, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, in PubMed, PsycINFO, Web of Science Core Collection, and the Cochrane Library. The quality of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations system. We further assessed aspects of feasibility and rated quality of interventions using criteria suggested by an expert panel on mental health care (German Association for Psychiatry, Psychotherapy, and Psychosomatics). A random-effects meta-analysis was conducted to assess between-group effect sizes.ResultsIn total, 9 trials (N=1349) were included. Of these, 7 studies were analyzed meta-analytically. Significant effects were found for symptoms of grief (g=0.54, 95% CI 0.32-0.77), depression (g=0.44, 95% CI 0.20-0.68), and posttraumatic stress (g=0.82, 95% CI 0.63-1.01). Heterogeneity was moderate for grief and depression (I2=48.75% and 55.19%, respectively) and low for posttraumatic stress symptoms (I2=0%). The overall quality of evidence was graded low (grief and depression) to moderate (posttraumatic stress). User satisfaction with the interventions was high, as was the quality of the interventions assessed using objective quality criteria.ConclusionsInternet- or mobile-based interventions might constitute an effective treatment approach against symptoms of grief in bereaved adults. However, the small sample sizes and limited number of studies included in the review warrant further investigation.Trial RegistrationInternational Prospective Register of Systematic Reviews (PROSPERO) CRD42012002100; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=131428

Donor Ventilation Parameters as Predictors for Length of Mechanical Ventilation after Lung Transplantation: Results of a Prospective Multicenter Study

<h3>Purpose</h3> The evaluation of donor lungs heavily depends on the subjective judgment of the retrieval surgeon. As a consequence, acceptance rates vary significantly among transplant centers. We aimed to determine donor ventilation parameters in a prospective study and test if they could be used as objective quality criteria during organ retrieval. <h3>Methods</h3> A prospective evaluation of lung donors was performed in three transplant centers. Ventilation parameters were collected at the time of retrieval using a standardized ventilation protocol. Recipient length of mechanical ventilation (LMV) was defined as the primary endpoint and collected data was used to build linear models predicting LMV. <h3>Results</h3> In total 166 donors were included in this study. Median LMV after transplantation was 32 hours (IQR:20-63). Peak inspiratory pressure (P_IP) and dynamic compliance (C_dyn) at the time of retrieval but not P/F ratio correlated with recipient LMV in Spearman correlations (r=0.280, p=0.002; r=-0.245, p=0.003 and r=0.064, p=0.432 respectively). Linear models were built to further evaluate the impact of donor ventilation parameters on LMV (table 1). The first model was based on donor P/F ratio, donor age, donor intubation time, donor smoking history, donor pCO2, aspiration, chest trauma and pathologic chest X-ray. This model performed poorly (multiple R-squared=0.063). In a second model, donor ventilation parameters were included and C_dyn was identified as the strongest predictor for LMV. The third model was extended by recipient factors, which significantly improved the robustness of the model (multiple R-squared=0.293). <h3>Conclusion</h3> In this prospective evaluation of donor lung parameters, currently used donor quality criteria poorly predicted recipient LMV. Our data suggest that C_dyn is a strong donor-bound parameter to predict short-term graft performance, however, recipient factors are similarly relevant.

Optimising and comparing source-extraction tools using objective segmentation quality criteria

Context. With the growth of the scale, depth, and resolution of astronomical imaging surveys, there is increased need for highly accurate automated detection and extraction of astronomical sources from images. This also means there is a need for objective quality criteria, and automated methods to optimise parameter settings for these software tools. Aims. We present a comparison of several tools developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects. In particular, we focus on evaluating performance in situations that present challenges for detection. For example, faint and diffuse galaxies; extended structures, such as streams; and objects close to bright sources. Furthermore, we develop an automated method to optimise the parameters for the above tools. Methods. We present four different objective segmentation quality measures, based on precision, recall, and a new measure for the correctly identified area of sources. Bayesian optimisation is used to find optimal parameter settings for each of the four tools when applied to simulated data, for which a ground truth is known. After training, the tools are tested on similar simulated data in order to provide a performance baseline. We then qualitatively assess tool performance on real astronomical images from two different surveys. Results. We determine that when area is disregarded, all four tools are capable of broadly similar levels of detection completeness, while only NoiseChisel and MTObjects are capable of locating the faint outskirts of objects. MTObjects achieves the highest scores on all tests for all four quality measures, whilst SExtractor obtains the highest speeds. No tool has sufficient speed and accuracy to be well suited to large-scale automated segmentation in its current form.

Tourism Affinity and Its Effects on Tourist and Resident Behavior

Anecdotal evidence suggests that tourists do not only choose tourism destinations based on objective quality criteria. Rather, tourists may be drawn to certain destinations for reasons such as feelings of connection or affinity. This article provides a first examination of tourism affinity (TAFF) and its effects on tourism behavior. Tourists who are high on TAFF feel sympathy, admiration, or attachment toward a given country. In addition to examining TAFF, we also test the impact of tourism animosity (TANI) on a variety of resident and tourism behaviors. The results show that TAFF is a positive driver of several tourism-related outcomes, such as word of mouth and resident hospitality, while TANI drives general intention to visit and provide word of mouth but is a barrier to closer interactions. In addition, goal compatibility, relative power, and moral obligation drive TAFF while relative power drives TANI.

Donor ventilation parameters as predictors for length of mechanical ventilation after lung transplantation: Results of a prospective multicenter study

The evaluation of donor lungs heavily depends on the subjective judgment of the retrieval surgeon. As a consequence, acceptance rates vary significantly among transplant centers. We aimed to determine donor ventilation parameters in a prospective study and test if they could be used as objective quality criteria during organ retrieval. A prospective evaluation of lung donors was performed in 3 transplant centers. Ventilation parameters were collected at the time of retrieval using a standardized ventilation protocol. Recipient length of mechanical ventilation (LMV) was defined as the primary end point, and collected data was used to build linear models predicting LMV. In total, 166 donors were included in this study. Median LMV after transplantation was 32 hours (interquartile range: 20-63 hours). Peak inspiratory pressure and dynamic compliance (Cdyn) at the time of retrieval, but not the partial pressure of oxygen/fraction of inspired oxygen (P/F) ratio, correlated with recipient LMV in Spearman correlations (r = 0.280, p = 0.002; r = -0.245, p = 0.003; and r = 0.064, p = 0.432, respectively). Linear models were built to further evaluate the impact of donor ventilation parameters on LMV. The first model was based on donor P/F ratio, donor age, donor intubation time, donor smoking history, donor partial pressure of carbon dioxide, aspiration, chest trauma, and pathologic chest X-ray. This model performed poorly (multiple R-squared = 0.063). In a second model, donor ventilation parameters were included, and Cdyn was identified as the strongest predictor for LMV. The third model was extended by recipient factors, which significantly improved the robustness of the model (multiple R-squared = 0.293). In this prospective evaluation of donor lung parameters, currently used donor quality criteria poorly predicted recipient LMV. Our data suggest that Cdyn is a strong donor-bound parameter to predict short-term graft performance; however, recipient factors are similarly relevant.

Generative adversarial network-based super-resolution of diffusion-weighted imaging: Application to tumour radiomics in breast cancer.

Diffusion-weighted imaging (DWI) is increasingly used to guide the clinical management of patients with breast tumours. However, accurate tumour characterization with DWI and the corresponding apparent diffusion coefficient (ADC) maps are challenging due to their limited resolution. This study aimed to produce super-resolution (SR) ADC images and to assess the clinical utility of these SR images by performing a radiomic analysis for predicting the histologic grade and Ki-67 expression status of breast cancer. To this end, 322 samples of dynamic enhanced magnetic resonance imaging (DCE-MRI) and the corresponding DWI data were collected. A SR generative adversarial (SRGAN) and an enhanced deep SR (EDSR) network along with the bicubic interpolation were utilized to generate SR-ADC images from which radiomic features were extracted. The dataset was randomly separated into a development dataset (n = 222) to establish a deep SR model using DCE-MRI and a validation dataset (n = 100) to improve the resolution of ADC images. This random separation of datasets was performed 10 times, and the results were averaged. The EDSR method was significantly better than the SRGAN and bicubic methods in terms of objective quality criteria. Univariate and multivariate predictive models of radiomic features were established to determine the area under the receiver operating characteristic curve (AUC). Individual features from the tumour SR-ADC images showed a higher performance with the EDSR and SRGAN methods than with the bicubic method and the original images. Multivariate analysis of the collective radiomics showed that the EDSR- and SRGAN-based SR-ADC images performed better than the bicubic method and original images in predicting either Ki-67 expression levels (AUCs of 0.818 and 0.801, respectively) or the tumour grade (AUCs of 0.826 and 0.828, respectively). This work demonstrates that in addition to improving the resolution of ADC images, deep SR networks can also improve tumour image-based diagnosis in breast cancer.

FFTMI: Features Fusion for Natural Tone-Mapped Images Quality Evaluation

Tone-mapping is a crucial step in the task towards displaying high dynamic range (HDR) images on standard displays. Given the number of possible ways to tone-map such images, development of an objective quality criterion, enabling selection of the most suitable tone-mapping operator (TMO) and setting its parameters in order to maximize the quality of the reproduction, is of high interest. In this paper, a new objective metric for natural tone-mapped images is proposed. It is based on a fusion of several perceptually relevant features that have been carefully selected using an appropriate feature selection procedure. The outcome of the selection also provides a valuable insight into the importance of particular perceptual aspects when judging the quality of tone-mapped HDR content. The performance of the resulting combination of features is thoroughly evaluated with respect to three publicly available databases and compared to several relevant state-of-the-art criteria. The proposed approach is shown to significantly outperform the tested metrics and can, therefore, be considered a competitive alternative for tone-mapped images evaluation.

37. PREIMPLANTATION GENETIC TESTING: TO THE OPEN QUESTIONS ABOUT DATA INTERPRETATION OBTAINED BY MASSIVE PARALLEL SEQUENCING

Introduction the accuracy results of preimplantation genetic testing of embryos for aneuploidy (PGT-A) by massive parallel sequencing directly depends on the effectiveness of the quality control. The aim of this study was to analyze the external and intralaboratory system of the quality assessment to optimize protocols, algorithms of troubleshooting and selection of the most informative objective criteria for the interpretation of the PGT-A results. Materials and methods we analyzed the quality criteria more than 2000 human bioptates of the trophectoderm cells. PGT-A was performed using VeriSeq reagent kits. Sequencing was performed with the Illumina Miseq instrument. Sequencing data analysis was done by BlueFuse Multi Software. External quality assessment of PGT-A was carried out through participation in the program of interlaboratory comparisons of the consortium UK NEQAS. Results with the aim of obtaining optimal performance of the sequencing was carried out intralaboratory validation of methods of libraries preparation for sequencing. In 10% of cases, genomic profiles, which were difficult to interpret, were obtained with optimal performance criteria of whole genome amplification (WGA) and the quality of subsequent sequencing. One of the problems is the suspicion of segmental aneuploidies in a mosaic version. Recognition of false mosaicism helps, in particular, the absence of chromosome break points, the stereotypical pattern of chromosome copy number variations (CNV), which may be associated with difficulties in reading of GC-rich DNA regions. As a result of participation in the program of external quality assessment of a consortium UK NEQAS we found that partial DNA degradation in the sample makes it impossible to detect trisomies. Furthermore, studying the PGT-A statistical results of different laboratories, attention is drawn to a significant spread in the frequency of mosaicism detected by them. This may be primarily due to the complexity of interpreting so-called noisy CNV charts. When analyzing the sequencing results using BlueFuse Multi software, the researcher is able to estimate for each sample the total overall noise score, as well as the Region Confidence value for each chromosome. However, the low information content of these parameters to estimate the number of copies of a single chromosome often generates subjectivity in the decision of the expert. In this regard, the most important task is to minimize the technical factors that can lead to the appearance of intense artifacts in CNV-charts, which complicates their interpretation. We, together with the adjacent laboratory in Moscow, have developed a research proposal, the implementation of which will help to shed light on the technical issues of all embryo and PGT-A stages currently remain elusive. Conclusions the main reason for obtaining difficult to interpret genomic profiles is the low quality of the original DNA and as a consequence – false positive or false negative results of PGT-A. To prevent false-positive and false-negative results of PGT-A, a complex analysis of objective quality criteria of different stages of PGT analysis is necessary due to the lack of the information content of each individual factor in case of moderately pronounced DNA degradation in the sample.

Simultaneous single- and multi-contrast super-resolution for brain MRI images based on a convolutional neural network

In magnetic resonance imaging (MRI), the acquired images are usually not of high enough resolution due to constraints such as long sampling times and patient comfort. High-resolution MRI images can be obtained by super-resolution techniques, which can be grouped into two categories: single-contrast super-resolution and multi-contrast super-resolution, where the former has no reference information, and the latter applies a high-resolution image of another modality as a reference. In this paper, we propose a deep convolutional neural network model, which performs single- and multi-contrast super-resolution reconstructions simultaneously. Experimental results on synthetic and real brain MRI images show that our convolutional neural network model outperforms state-of-the-art MRI super-resolution methods in terms of visual quality and objective quality criteria such as peak signal-to-noise ratio and structural similarity.

PepsNMR for 1H NMR metabolomic data pre-processing

In the analysis of biological samples, control over experimental design and data acquisition procedures alone cannot ensure well-conditioned 1H NMR spectra with maximal information recovery for data analysis. A third major element affects the accuracy and robustness of results: the data pre-processing/pre-treatment for which not enough attention is usually devoted, in particular in metabolomic studies. The usual approach is to use proprietary software provided by the analytical instruments' manufacturers to conduct the entire pre-processing strategy. This widespread practice has a number of advantages such as a user-friendly interface with graphical facilities, but it involves non-negligible drawbacks: a lack of methodological information and automation, a dependency of subjective human choices, only standard processing possibilities and an absence of objective quality criteria to evaluate pre-processing quality. This paper introduces PepsNMR to meet these needs, an R package dedicated to the whole processing chain prior to multivariate data analysis, including, among other tools, solvent signal suppression, internal calibration, phase, baseline and misalignment corrections, bucketing and normalisation. Methodological aspects are discussed and the package is compared to the gold standard procedure with two metabolomic case studies. The use of PepsNMR on these data shows better information recovery and predictive power based on objective and quantitative quality criteria. Other key assets of the package are workflow processing speed, reproducibility, reporting and flexibility, graphical outputs and documented routines.

Multi-station basis for Polar Cap (PC) indices: ensuring credibility and operational reliability

The Polar Cap (PC) indices, PCN (North) and PCS (South) are based on polar geomagnetic observations from Qaanaaq (Thule) and Vostok, respectively, processed to measure the transpolar plasma convection that may seriously affect space weather conditions. To establish reliable space weather forecasts based on PC indices, and also to ensure credibility of their use for scientific analyses of solar wind-magnetosphere interactions, additional sources of data for the PC indices are investigated. In the search for alternative index sources, objective quality criteria are established here to be used for the selection among potential candidates. These criteria are applied to existing PC index series to establish a quality scale. In the Canadian region, the data from Resolute Bay magnetometer are shown to provide alternative PCN indices of adequate quality. In Antarctica, the data from Concordia Dome-C observatory are shown to provide basis for alternative PCS indices. In examples to document the usefulness of these alternative index sources it is shown that PCN indices in a real-time version based on magnetometer data from Resolute Bay could have given 6 h of early warning, of which the last 2 h were “red alert”, up to the onset of the strong substorm event on 13 March 1989 that caused power outage in Quebec. The alternative PCS indices based on data from Dome-C have helped to disclose that presently available Vostok-based PCS index values are corrupted throughout most of 2011.

Multi-Contrast Brain MRI Image Super-Resolution With Gradient-Guided Edge Enhancement

In magnetic resonance imaging (MRI), the super-resolution technology has played a great role in improving image quality. The aim of this paper is to improve edges of brain MRI by incorporating the gradient information of another contrast high-resolution image. Multi-contrast images are assumed to possess the same gradient direction in a local pattern. We proposed to establish a relation model of gradient value between different contrast images to restore a high-resolution image from its input low-resolution version. The similarity of image patches is employed to estimate intensity parameters, leading a more accurate reconstructed image. Then, an iterative back-projection filter is applied to the reconstructed image to further increase the image quality. The new approach is verified on synthetic and real brain MRI images and achieves higher visual quality and higher objective quality criteria than the compared state-of-the-art super-resolution approaches. The gradient information of the multi-contrast MRI images is very useful. With a proper relation model, the proposed method enhances image edges in MRI image super-resolution. Improving the MRI image resolution from very low-resolution observations is challenging. We tackle this problem by first modeling the relation of gradient value in multi-contrast MRI and then performing fast supper-resolution methods. This relation model may be helpful for other MRI reconstruction problems.

Performance evaluation of error control schemes for distributed video coding over wireless multimedia sensor networks

Distributed Video Coding (DVC) is a new approach in video coding which due to low computational complexity at the encoder side, has a great potential to be used in Wireless Multimedia Sensor Networks (WMSN). However, the different architecture of this codec affects the efficiency of transmission protocols and in order to efficient transmission of DVC over WMSN, it is necessary to evaluate the performance of the transmission protocols in the presence of DVC characteristics. In the view of these protocols, error control methods are important mechanisms that provide quality of service and robust multimedia communications. For this reason, we performed a comparative performance analysis for all error control schemes that consist of Automatic Repeat Request (ARQ), Forward Error Correction (FEC), Erasure Coding (EC), hybrid link layer ARQ/FEC and multi-layer hybrid error control schemes for DVC in WMSNs. These analyses are in the terms of the most importance metrics in multimedia communications over WSNs, such as objective and subjective video quality criteria, delay, energy consumption and some DVC-specific metrics. The results show the distinct behavior of DVC in the presence of channel error and can be used to propose an effective and efficient error control scheme for DVC over WMSN.

Calibration of coronary calcium scores determined using iterative image reconstruction (AIDR 3D) at 120, 100, and 80 kVp.

Computed tomography (CT) radiation dose reduction is frequently achieved by applying lower tube voltages and using iterative reconstruction (IR). For calcium scoring, the reference protocol at 120 kVp with filtered back projection (FBP) is still used, because kVp and IR may influence the Agatston score (AS) and volume score (VS). The authors present a two-step method to optimize dose: first, to determine the lowest feasible exposure and highest noise thresholds; second, to define a calibration method that ensures that the AS and VS are similar to the reference protocol. AS and VS were measured for an anthropomorphic thoracic phantom that includes a calcium calibration module. The phantom was scanned on a 320-row CT scanner, at tube voltages of 120 kVp using FBP, and 120, 100, and 80 kVp using adaptive iterative dose reduction (AIDR 3D) reconstruction. The minimum CTDIs were determined based on three objective quality criteria. Calibration was performed to estimate adjusted CT number thresholds for the lower kVp acquisitions. Finally, the accuracies of the total and individual insert scores at dose level close to the minimum CTDI level were investigated and compared to low (FBPLD - 120) and high (FBPHD - 120) dose reference protocols (based on ten repeated acquisitions for each group). IR allows the exposure to be reduced by 69% at 120 kVp, with no significant effect on the total scores when averaged over all included dose steps and compared to FBP-120 (AS: 693 vs 699, p = 0.182; VS: 588 vs 587 mm(3), p = 0.569). Also when averaged over ten repeated scans and compared to FBPHD - 120 (AS: 709 vs 704, p = 0.435; VS: 604 vs 601 mm(3), p = 0.479), there is no statistical significant effect. Reducing the peak tube voltage allows even greater dose reductions: 73% at 100 kVp and 76% at 80 kVp. The calibrated CT number thresholds for analysis at 120, 100, and 80 kVp were, respectively, 130, 133, and 160 HU for the Agatston score, and 130, 132, and 140 HU for the volume score. Following the calibration, the mean scores of the four groups with dose variation were not significantly different from the reference protocol, at 100 kVp (AS: 698 vs 699, p = 0.818; VS: 584 vs 587 mm(3), p = 0.365) or at 80 kVp (AS: 698 vs 699, p = 0.996; VS: 586 vs 587 mm(3), p = 0.827). Similarly, there was no significant score difference with FBPLD - 120 during repeated scanning: 100 kVp (AS: 690 vs 694, p = 0.394; VS: 579 vs 585 mm(3), p = 0.168) and 80 kVp (AS: 703 vs 694, p = 0.115; VS: 588 vs 585 mm(3), p = 0.613). Compared to FBPHD - 120 group, the relative score deviation for the accuracy of the 400 and 800 mg/cm(3) HA inserts with 3 and 5 mm diameter is less than 7%. However, the relative deviation of the smaller 1 mm inserts is poorer (up to 41% deviations for scores <3). With iterative reconstruction using AIDR 3D, deviations of the total Agatston and volume scores remain within 4% of the reference protocol. The 1 mm inserts were detected as calcification, but scores less than ten tend to be underestimated. Following the calibration process, the application of IR in combination with reduced tube voltages allows up to 76% lower radiation dose.

Voicing of animated GIF by data hiding

GIF animations are silent image sequences widely used on the web thanks to their wide support and portability. In this work, we propose an original technique based on data hiding, to add sound tracks in GIF animations. Data hiding is usually used to embed security codes in a host medium to prevent from illegal copying or to protect copyrights (watermarking) or to send secret messages to a dedicated receiver (steganography). We propose to use host GIF images as a transmission channel to convey hidden sound bits with lowest perceptual image distortion and without altering the wide portability of the GIF format, by means of data hiding. The inserted bits are neither secret nor intended for security issues. They are intended to be played by an audio player synchronously with the GIF player to add sound to the GIF animation. The embedding process is a low complexity, luminance based steganography algorithm, that slightly modifies the pixels colors of the GIF images to insert the sound bits. The extraction of the inserted audio is completely blind: the audio is directly extracted from the pixels of each cover image. The proposed GIF voicing was tested with different GIF sequences (cartoons and real scenes) and no audio degradation was reported while a slight, most imperceptible, color modification was noticed in case of an important amount of inserted data. The cover images have undergone objective quality criteria and informal subjective evaluation and has proved to be of good quality.