Existing Quality Metrics Research Articles

Internal generative mechanism driven blind quality index for deblocked images

Blocking artifact is one of the most common distortion types in JPEG compression. Extensive deblocking algorithms have been proposed to improve the quality of JPEG compressed images. However, very little work has been dedicated to the quality assessment of deblocked images, which may hinder further development of image deblocking techniques. The deblocked images are usually contaminated by multiple distortions, typically blocking artifacts and blur. Although various quality metrics have been reported, they are not designed specially for deblocked images, so they cannot accurately predict the quality of deblocked images. To fill this gap, we propose a new quality metric for deblocked images. Inspired by the internal generative mechanism theory, a deblocked image is first decomposed into two portions, i.e., the predicted and disorderly portions. Then the distortions in the two portions are evaluated separately. For the predicted portion, the distortion-specific features are extracted to separately evaluate blocking artifacts and blur in the spatial domain. Then the joint effect of blocking artifacts and blur is evaluated by extracting energy-based features in the Curvelet domain. For the disorderly portion, R $\acute {\textbf {e}}$ nyi entropy is employed to measure the uncertain information introduced in the deblocking process. Finally, all features are combined to train a random forest model for quality prediction of deblocked images. Experimental results conducted on a newly released DeBlocked Image Database (DBID) demonstrate the superiority of the proposed method over the existing quality metrics. Moreover, the proposed metric is less dependent on the number of training images.

Color Contrast-Preserving Decolorization.

Decolorization is to convert a color image into a gray scale image while preserve image features like salient structure and chrominance contrast. The sign of the color contrast is crucial for the decolorization algorithm and is usually determined in existing works by giving a strict defined color order or twomode weak order. In this paper, a fast computation on color order is achieved via a simple global mapping which is introduced in a linear parametric model using an extended structure transfer filter. The values of the parameters are obtained via an elegant approximation method. A local decolorization algorithm is finally designed on basis of the global linear mapping so that both color and spatial information are preserved robustly and accurately. Experimental results show that the proposed decolorization algorithms obtain a good performance among existing quality metrics for the decolorization. In addition, the proposed global decolorization algorithm is friendly to mobile devices with limited computational resource.

Perceptual quality evaluation for motion deblurring

Motion deblurring has been widely studied. However, the relevant quality evaluation of motion deblurred images remains an open problem. The motion deblurred images are usually contaminated by noise, ringing and residual blur (NRRB) simultaneously. Unfortunately, most of the existing quality metrics are not designed for multiply distorted images, so they are limited in predicting the quality of motion deblurred images. In this study, the authors propose a new quality metric for motion deblurred images by measuring NRRB. For a motion deblurred image, the noise level is first estimated. Then the ringing effect is measured by incorporating visual saliency model to adapt to the characteristic of the human visual system. A reblurring‐based method is proposed to extract similarity features between a motion deblurred image and its re‐blurred version for evaluating the residual blur. Finally, the overall quality score of a motion deblurred image is obtained by pooling the scores of noise, ringing and blur. Experimental results conducted on a motion deblurring database demonstrate that the proposed metric significantly outperforms the existing quality metrics. In addition, the proposed NRRB metric is used for improving the existing general‐purpose no‐reference metrics, and very encouraging results are achieved.

Quality Assessment of DIBR-Synthesized Images by Measuring Local Geometric Distortions and Global Sharpness

Depth-image-based rendering (DIBR) is a fundamental technique in free viewpoint video, which is widely adopted to synthesize virtual viewpoints. The warping and rendering operations in DIBR generally introduce geometric distortions and sharpness change. The state-of-the-art quality indices are limited in dealing with such images since they are sensitive to geometric changes. In this paper, a new quality model for DIBR-synthesized view images is presented by measuring LOcal Geometric distortions in disoccluded regions and global Sharpness (LOGS). A disoccluded region detection method is first proposed using SIFT-flow-based warping. Then, the sizes and distortion strength of local disoccluded regions are combined to generate a score. Furthermore, a reblurring-based strategy is proposed to quantify the global sharpness. Finally, the overall quality score is calculated by pooling the scores of local disoccluded regions and global sharpness. Experiments on four public DIBR-synthesized image/video databases show the superiority of the proposed metric over the state-of-the-art quality models. The proposed method is further adopted for boosting the performances of existing quality metrics and benchmarking DIBR algorithms, both achieving very promising results.

21. Assessing image quality of kilo-voltage cone beam CT (kV-CBCT) for adaptive radiotherapy

Introduction The scope of this study was to review and compare quality of kV-CBCT imaging highlighted from different generation systems and their respective main issues in regards with fan-beam CT (FBCT). Indeed kV-CBCT beam geometry is different from FBCT, introducing much more artefacts and leading to inaccuracies to convert Hounsfield Units (HU) into the relative electron density. This should be explored in depth because kV-CBCT is potentially the reference data for new approaches such computation of the daily actual delivered dose. Methods Different kV-CBCT acquisition modes with various tube voltage (kV) and exposure (mAs) were studied: “pelvis” and “pelvis obese” with a Varian Truebeam™ (unit 1), “pelvis” and “low dose thorax” with a Varian Clinac 2100CD (unit 2). Using the TomoTherapy® Cheese phantom (Gammex RMI, Middleton, WI) for HU to electron density (de) calibration curve, and the NEMA body water phantom for HU uniformity, noise and mean water number analysis, were investigated. From the FBCT and kV-CBCT HU differential histograms, frequency peaks representing water, air, lung, soft tissue and bone were compared. Results For unit 2, streaking and ring artifacts are much greater than for unit 1 as well as HU uniformity is deteriorated. Noise values are comparable between units but standard deviation is twice at unit 2. Peaks observed in the differential histograms are broader in kV-CBCT than those of FBCT especially for high tissue density. kV-CBCT uniformity is more degraded than in FBCT because CBCT is more prone to artefacts in images such as: streaking, cupping, or ring artifacts. Variations in calibration protocols were observed between FBCT and kV-CBCT that could explain differences for mean water number. Conclusions The two commercial kV-CBCT systems demonstrate different performances. We found that HU differential histograms are an efficient way for comparing and controlling image quality in addition to existing quality metrics.

No-reference quality assessment of compressive sensing image recovery

Compressive sensing (CS) has been attracting tremendous attention in recent years. Extensive CS image recovery algorithms have been proposed for more effective image reconstruction. However, very little work has been addressed for the quality assessment of CS recovered images, which may hinder further development of CS image recovery techniques. The CS recovered images are typically contaminated by multiple distortions, particularly at low sampling rates. Unfortunately, the existing quality metrics are ineffective for evaluating multiple distortions, so they are limited in predicting the quality of CS recovered images. Motivated by this, this paper presents a no-reference CS Recovered Image Quality (CSRIQ) metric based on the measurement of both local and global distortions in CS recovered images. The local features consist of a local phase coherence based edge sharpness measure and a gray level co-occurrence matrix based texture measure. The global features are extracted based on the natural scene statistics and can be divided into two types. One type is obtained by calculating image naturalness parameters. The other type is computed based on the statistics of singular value decomposition coefficients. Support vector regression is employed to do model training and the subsequent quality prediction. Experimental results conducted on a CS recovered image database demonstrate the advantages of the proposed method. As a application, the proposed metric is used for automatic parameter selection for CS image recovery algorithms.

Evaluating Hex‐mesh Quality Metrics via Correlation Analysis

AbstractHexahedral (hex‐) meshes are important for solving partial differential equations (PDEs) in applications of scientific computing and mechanical engineering. Many methods have been proposed aiming to generate hex‐meshes with high scaled Jacobians. While it is well established that a hex‐mesh should be inversion‐free (i.e. have a positive Jacobian measured at every corner of its hexahedron), it is not well‐studied that whether the scaled Jacobian is the most effective indicator of the quality of simulations performed on inversion‐free hex‐meshes given the existing dozens of quality metrics for hex‐meshes. Due to the challenge of precisely defining the relations among metrics, studying the correlations among different quality metrics and their correlations with the stability and accuracy of the simulations is a first and effective approach to address the above question. In this work, we propose a correlation analysis framework to systematically study these correlations. Specifically, given a large hex‐mesh dataset, we classify the existing quality metrics into groups based on their correlations, which characterizes their similarity in measuring the quality of hex‐elements. In addition, we rank the individual metrics based on their correlations with the accuracy and stability metrics for simulations that solve a number of elliptic PDE problems. Our preliminary experiments suggest that metrics that assess the conditioning of the elements are more correlated to the quality of solving elliptic PDEs than the others. Furthermore, an inversion‐free hex‐mesh with higher average quality (measured by any quality metrics) usually leads to a more accurate and stable computation of elliptic PDEs. To support our correlation study and address the lack of a publicly available large hex‐mesh dataset with sufficiently varying quality metric values, we also propose a two‐level perturbation strategy to generate the desired dataset from a small number of meshes to exclude the influences of element numbers, vertex connectivity, and volume sizes to our study.

947 Polypectomy Competency Varies Between Endoscopists and Does Not Adequately Correlate With Existing Quality Metrics

947 Polypectomy Competency Varies Between Endoscopists and Does Not Adequately Correlate With Existing Quality Metrics

Development of a Patient-centered Outcome Measure for Emergency Department Asthma Patients.

Measuring outcomes of emergency care is of key importance, but current metrics, such as 72-hour return visit rates, are subject to ascertainment bias, incentivize overtesting and overtreatment at initial visit, and do not reflect the full burden of disease and morbidity experienced at home following ED care. There is increasing emphasis on including patient-reported outcomes, but the existing patient-reported measures have limited applicability to emergency care. The objective was to identify concepts for inclusion in a patient-reported outcome measure for ED care and assess differences in potential concepts by health literacy. A three-phase qualitative study was completed using freelisting and semistructured interviewing for concept identification, member checking for concept ranking, and cognitive interviewing for question development. Participants were drawn from three tertiary care EDs. Parents of patients (pediatric) or patients (adult) with asthma completed a demographic survey and an assessment of health literacy. Phase 1 participants also completed a freelisting exercise and qualitative interview regarding the definition of success following ED discharge. Phase 2 participants completed a member checking survey based on concepts identified in Phase 1. Phase 3 was a pilot of trial questions based on the highest-ranked concepts from Phase 2. Phase 1 enrolled 22 adult patients and 37 parents of pediatric patients. Phase 2 enrolled 41 adult patients and 200 parents. Phase 3 involved 15 parents. Across all demographic/literacy groups, Phase 1 participants reported return to usual activity and lack of asthma symptoms as the most important markers of success. In Phase 2, symptom improvement, medication use and access, and asthma knowledge were identified as the most important components of the definition of post-ED discharge success. Phase 3 resulted in five questions for the proposed measure. A stepwise qualitative process can identify, rank, and formulate questions based on patient-identified concepts for inclusion in a patient-reported outcome measure for ED discharge. The four key concepts identified for inclusion: symptom improvement, medication access, correct medication use, and asthma knowledge are not measured by existing quality metrics.

Using quality improvement to increase human milk use for preterm infants

This review will provide an overview of quality improvement methods that have been used to improve human milk use (mother's own milk and donor milk) for very low-birth-weight infants in the hospital setting in the last decade. We will review the following: (1) evidence-based practices known to increase mother's own milk for very low-birth-weight infants; (2) individual hospitals with exemplary lactation programs and past and current US-based statewide quality improvement collaboratives focused on increasing mother's own milk; and (3) existing quality metrics for human milk and gaps in metrics. Finally, we will provide practical examples of key driver diagrams and change concepts that may be used to inform quality improvement for mother's own milk for very low-birth-weight infants.

Identification of Emergency Department Visits in Medicare Administrative Claims: Approaches and Implications.

Administrative claims data sets are often used for emergency care research and policy investigations of healthcare resource utilization, acute care practices, and evaluation of quality improvement interventions. Despite the high profile of emergency department (ED) visits in analyses using administrative claims, little work has evaluated the degree to which existing definitions based on claims data accurately captures conventionally defined hospital-based ED services. We sought to construct an operational definition for ED visitation using a comprehensive Medicare data set and to compare this definition to existing operational definitions used by researchers and policymakers. We examined four operational definitions of an ED visit commonly used by researchers and policymakers using a 20% sample of the 2012 Medicare Chronic Condition Warehouse (CCW) data set. The CCW data set included all Part A (hospital) and Part B (hospital outpatient, physician) claims for a nationally representative sample of continuously enrolled Medicare fee-for-services beneficiaries. Three definitions were based on published research or existing quality metrics including: 1) provider claims-based definition, 2) facility claims-based definition, and 3) CMS Research Data Assistance Center (ResDAC) definition. In addition, we developed a fourth operational definition (Yale definition) that sought to incorporate additional coding rules for identifying ED visits. We report levels of agreement and disagreement among the four definitions. Of 10,717,786 beneficiaries included in the sample data set, 22% had evidence of ED use during the study year under any of the ED visit definitions. The definition using provider claims identified a total of 4,199,148 ED visits, the facility definition 4,795,057 visits, the ResDAC definition 5,278,980 ED visits, and the Yale definition 5,192,235 ED visits. The Yale definition identified a statistically different (p < 0.05) collection of ED visits than all other definitions including 17% more ED visits than the provider definition and 2% fewer visits than the ResDAC definition. Differences in ED visitation counts between each definition occurred for several reasons including the inclusion of critical care or observation services in the ED, discrepancies between facility and provider billing regulations, and operational decisions of each definition. Current operational definitions of ED visitation using administrative claims produce different estimates of ED visitation based on the underlying assumptions applied to billing data and data set availability. Future analyses using administrative claims data should seek to validate specific definitions and inform the development of a consistent, consensus ED visitation definitions to standardize research reporting and the interpretation of policy interventions.

Hospital readmission as a quality measure in surgery.

The debate aboutwhether hospital readmissions should be used to measure quality is escalating. The renewed interest in this topic comes fromthe recognition that reducing readmissions is a rare example of the elusive goal of simultaneously improving quality and reducingcosts. TheCenters forMedicare&MedicaidServices (CMS) recentlygavereadmissionmeasures increased importanceby implementing substantial financial penalties through the Hospital Readmissions Reduction Program (HRRP). The HRRP began assessing penaltiesofupto3%ofahospital’s totalMedicarepayments forhospitalswithhigher-than-expected risk-adjusted readmission rates for commonmedical conditions, acutemyocardial infarction, pneumonia, and congestive heart failure.1 Whether hospital readmissions are a good measure of quality for these medical conditions is hotly debated. Many argue against using them because readmissions are not correlated with known quality metrics, such as mortality, volume, or process compliance. Others are concerned that readmissions have more to do with the financial and social resources of the patient than theydowith quality of care.1 Proponents argue that readmissions are not correlated with existing quality metrics because they represent a unique domain of quality—coordination of care. In other words, readmission servesasaproxy forhowwell thehospitalpreparespatients for transitioning from one setting to another. With CMS set to expand these penalties to surgical procedures in 2015, a similar argument has arisen in surgery.2 Many have criticized the use of readmissions in surgical populations, but these criticisms are largely based on the same arguments against using readmissions as quality metrics for medical conditions.2 However, there is emerging evidence that medical and surgical readmissions should be considered separately because they may have different root causes. ArecentstudybyMorrisetal3 inJAMASurgerysupports theview that hospital readmissions may indeed be a valid measure of hospital quality in surgery. Likemanyprior studies, the authors showed that patients who experienced a postoperative complication were at higher risk for readmission.4 Importantly, however, the investigatorswere able to study the timingof the complication. The investigators found that 72% of complications occurred prior to disJAMASURGERY

Sepsis mandates: improving inpatient care while advancing quality improvement.

Sepsis mandates: improving inpatient care while advancing quality improvement.

New measurements reveal weaknesses of image quality metrics in evaluating graphics artifacts

Reliable detection of global illumination and rendering artifacts in the form of localized distortion maps is important for many graphics applications. Although many quality metrics have been developed for this task, they are often tuned for compression/transmission artifacts and have not been evaluated in the context of synthetic CG-images. In this work, we run two experiments where observers use a brush-painting interface to directly mark image regions with noticeable/objectionable distortions in the presence/absence of a high-quality reference image, respectively. The collected data shows a relatively high correlation between the with-reference and no-reference observer markings. Also, our demanding per-pixel image-quality datasets reveal weaknesses of both simple (PSNR, MSE, sCIE-Lab) and advanced (SSIM, MS-SSIM, HDR-VDP-2) quality metrics. The most problematic are excessive sensitivity to brightness and contrast changes, the calibration for near visibility-threshold distortions, lack of discrimination between plausible/implausible illumination, and poor spatial localization of distortions for multi-scale metrics. We believe that our datasets have further potential in improving existing quality metrics, but also in analyzing the saliency of rendering distortions, and investigating visual equivalence given our with- and no-reference data.

Paying for Quality Not Quantity: A Wisconsin Health Maintenance Organization Proposes an Incentive Model for Reimbursement of Chiropractic Services

ObjectiveThe purpose of this study is to describe a reimbursement model that was developed by one Health Maintenance Organization (HMO) to transition from fee-for-service to add a combination of pay for performance and reporting model of reimbursement for chiropractic care. MethodsThe previous incentive program used by the HMO provided best-practice education and additional reimbursement incentives for achieving the National Committee for Quality Assurance Back Pain Recognition Program (NCQA-BPRP) recognition status. However, this model had not leveled costs between doctors of chiropractic (DCs). Therefore, the HMO management aimed to develop a reimbursement model to incentivize providers to embrace existing best-practice models and report existing quality metrics. The development goals included the following: it should (1) be as financially predictable as the previous system, (2) cost no more on a per-member basis, (3) meet the coverage needs of its members, and (4) be able to be operationalized. The model should also reward DCs who embraced best practices with compensation, not simply tied to providing more procedures, the new program needed to (1) cause little or no disruption in current billing, (2) be grounded achievable and defined expectations for improvement in quality, and (3) be voluntary, without being unduly punitive, should the DC choose not to participate in the program. ResultsThe generated model was named the Comprehensive Chiropractic Quality Reimbursement Methodology (CCQRM; pronounced “Quorum”). In this hybrid model, additional reimbursement, beyond pay-for-procedures will be based on unique payment interpretations reporting selected, existing Physician Quality Reporting System (PQRS) codes, meaningful use of electronic health records, and achieving NCQA-BPRP recognition. This model aims to compensate providers using pay-for-performance, pay-for-quality reporting, pay-for-procedure methods. ConclusionThe CCQRM reimbursement model was developed to address the current needs of one HMO that aims to transition from fee-for-service to a pay-for-performance and quality reporting for reimbursement for chiropractic care. This model is theoretically based on the combination of a fee-for-service payment, pay for participation (NCQA Back Pain Recognition Program payment), meaningful use of electronic health record payment, and pay for reporting (PQRS-BPMG payment). Evaluation of this model needs to be implemented to determine if it will achieve its intended goals.

Assessing the quality of scientific conferences based on bibliographic citations

Assessing the quality of scientific conferences is an important and useful service that can be provided by digital libraries and similar systems. This is specially true for fields such as Computer Science and Electric Engineering, where conference publications are crucial. However, the majority of the existing quality metrics, particularly those relying on bibliographic citations, has been proposed for measuring the quality of journals. In this article we conduct a study about the relative performance of existing journal metrics in assessing the quality of scientific conferences. More importantly, departing from a deep analysis of the deficiencies of these metrics, we propose a new set of quality metrics especially designed to capture intrinsic and important aspects related to conferences, such as longevity, popularity, prestige, and periodicity. To demonstrate the effectiveness of the proposed metrics, we have conducted two sets of experiments that contrast their results against a “gold standard” produced by a large group of specialists. Our metrics obtained gains of more than 12% when compared to the most consistent journal quality metric and up to 58% when compared to standard metrics such as Thomson’s Impact Factor.

Layer-encoded video in scalable adaptive streaming

Combining the concepts of caching and transmission control protocol (TCP)-friendly streaming of layer-encoded video bears the problem that those videos might not be cached in full quality. Therefore, we focus in this work on the scheduling of retransmissions of missing segments of a cached video in a manner that allows clients to receive the content in an improved quality. In a first step, we conducted subjective assessments of variations in layer-encoded video with the goal to validate existing quality metrics, including our own, which are based on certain assumptions. A statistical analysis of the subjective assessment validates these assumptions. We also show that the frequently used peak signal-to-noise ratio (PSNR) is not an appropriate metric for variations in layer-encoded video. With the insight from the subjective assessment we develop heuristics for retransmission scheduling and prove their applicability by conducting a series of simulations.

Requirements For Systems Engineering Metrics

AbstractA systems engineering approach to the development of metrics for systems engineering is presented. Metrics are needed to indicate the “health” of an ongoing systems engineering process and the likely “quality” of the product of that process. A literature review of existing quality metrics identified four eras (1) inspection, (2) statistical quality control, (3) quality assurance, and (4) strategic quality management. The specific application of quality concepts to “white collar quality”, “engineering management quality”, and “system engineering quality” provided increasingly detailed and specialized product and process metrics. A survey of 28 agency/companies practicing systems engineering was made to determine whether the current solutions satisfied the functions and requirements of metrics identified in the literature. A set of 30 process and product metrics were analyzed in function, requirement and solution format. Collection, analysis, reporting and management operational functions were found to be as important as the choice of specific metrics.