Visual Image Quality Assessment Research Articles

Image Quality Assessment and Radiation exposure in Intra Oral Dental Radiography

In this study, an intra oral dental unit (Siemens-70) at King Abdul Aziz University (KAU) Dental Hospital was selected and investigated for visual image quality assessment and radiation protection purposes. Radiation dosimetry for determining the optimum image quality with the lowest radiation exposure to the patient was carried out. A DXTTR dental radiography trainer phantom head and neck, portable survey meter Model RAD EYE-B20, and radiation dosimetry system RADCAL Acuu-pro were used in this study. RADCAL Accu-pro is a non-invasive kV system, reliable instruments to measure and diagnose all X-ray machines including dental units. The radiation exposure to patients in (mGy) was measured using RADCAL ionization chamber Model 10×6-6. The best image quality with the lowest exposure dose was assessed for conventional intraoral X-ray film (Kodak type E) and the digital processing sensor (RVG 5200). Radiation survey level was done during this study for safety and protection purposes.

Imaging quality assessment of mammograms

The aim. The aim of the work is imaging quality assessment of pathological structures on the low-contrast gray-scale images of the mammary gland by developing a new method for multicriteria estimation of the mammograms quality.Solving methods. A method for multicriteria estimation of the visualization mammograms quality was developed. It is based on expert assessments and taking into account both subjective and objective characteristics of the mammographic images.Different criteria for optimality in the conditions of uncertainty is proposed to use for the comparison of average expert estimates of the mammographic image quality resulting from the different processing methods.Results. The proposed method for multicriteria evaluation of the visualization mammograms quality has been tested on real digital mammography images, which were obtained with the help of mammography complex Syma.The results of a comparative study of mammograms before and using various digital processing techniques have shown that the most optimal for radiologist perception and correct diagnosis is mammography image, which is processed by a method for enhancing imaging quality mammograms IMRI-MAM.Conclusions Thus, the application of the method for multicriteria evaluation of the visualization mammograms quality with the help of integrated scales allows to quickly and accurately carry out a visual assessment of the mammographic image quality. The proposed method will get rid of the time-consuming and inaccurate assessment of the modern imaging techniques only by subjective assessment.

Binocular visual characteristics-based stereoscopic image quality assessment metric for 3D video system

Compared with two-dimensional image quality assessment 2D-IQA, stereoscopic IQA SIQA has to take the binocular perception into consideration. In this paper, a new SIQA metric is proposed for three-dimensional video systems, which is based on binocular visual characteristics and contains two parts: binocular perceptual distortion evaluation BPDE and stereoscopic evaluation SE. To get the results of the BPDE and SE, a simple-complex cell along with different human visual system characteristics are used to compute the quality of binocular fusion maps and disparity maps between original and distorted stereoscopic image pairs. The final quality score is obtained by a nonlinear combination of BPDE value and SE value. Experimental results show that proposed SIQA metric in which the Pearson linear correlation coefficient PLCC and Spearman rank order correlation coefficient SROCC exceed 0.94 and 0.93 outperform current 2D-IQA and SIQA metrics.

Binocular visual characteristics-based stereoscopic image quality assessment metric for 3D video system

Binocular visual characteristics-based stereoscopic image quality assessment metric for 3D video system

BRIQA: Framework for the Blind and Referenced Visual Image Quality Assessment

Our proposal is to present a Blind and Referenced Image Quality Assessment or BRIQA. Thus, the main proposal of this paper is to propose an Interface, which contains not only a Full-Referenced Image Quality Assessment (IQA) but also a No- Referenced or Blind IQA applying perceptual concepts by means of Contrast Band-Pass Filtering (CBPF). Then, this proposal consists in contrast a degraded input image with the filtered versions of several distances by a CBPF, which computes some of the Human Visual System (HVS) variables. If BRIQA detects only one input, it performs a Blind Image Quality Assessment, on the contrary if BRIQA detects two inputs, it considers that a Referenced Image Quality Assessment will be computed. Thus, we first define a Full-Reference IQA and then a No-Reference IQA, which correlation is important when is contrasted with the psychophysical results performed by several observers. BRIQA weights the Peak Signal-to-Noise Ratio by using an algorithm that estimates some properties of the Human Visual System. Then, we compare BRIQA algorithm not only with the mainstream estimator in IQA, PSNR, but also state-of-the-art IQA algorithms, such as Structural SIMilarity (SSIM), Mean Structural SIMilarity (MSSIM), Visual Information Fidelity (VIF), etc. Our experiments show that the correlation of BRIQA correlated with PSNR is important, but this proposal does not need imperatively the reference image in order to estimate the quality of the recovered image.

No-Reference Perceived Image Quality Algorithm for Demosaiced Images

Visual image quality assessment (IQA) plays a key role in every multimedia application, as end user to it is a human-being. Real time applications demand no reference (NR) IQA, due to unavailability of the reference image. Today, most of the perceived/visual NR-IQA algorithms developed are for distortions like blur, ringing, and blocking artifacts. Very few are available for color distortions. Visible color distortions, such as false color, and zipper are produced in the demosaiced image due to incorrect interpolation of missing color values. In this paper, state of the art zipper and false color artifact quantification algorithms, general purpose NR-IQA algorithms are evaluated for visual quality assessment of demosaiced images. Separate NR- IQA algorithms are proposed for zipper and false color artifact quantification these scores are then combined to obtain final quality score for demosaiced image. Zipper algorithm quantifies zipper artifact by searching for zipper pixels in an image. While, false color algorithm finds correlation between local high frequency region’s color planes to quantify false color.

Human Visual System-Based Fundus Image Quality Assessment of Portable Fundus Camera Photographs.

Telemedicine and the medical "big data" era in ophthalmology highlight the use of non-mydriatic ocular fundus photography, which has given rise to indispensable applications of portable fundus cameras. However, in the case of portable fundus photography, non-mydriatic image quality is more vulnerable to distortions, such as uneven illumination, color distortion, blur, and low contrast. Such distortions are called generic quality distortions. This paper proposes an algorithm capable of selecting images of fair generic quality that would be especially useful to assist inexperienced individuals in collecting meaningful and interpretable data with consistency. The algorithm is based on three characteristics of the human visual system--multi-channel sensation, just noticeable blur, and the contrast sensitivity function to detect illumination and color distortion, blur, and low contrast distortion, respectively. A total of 536 retinal images, 280 from proprietary databases and 256 from public databases, were graded independently by one senior and two junior ophthalmologists, such that three partial measures of quality and generic overall quality were classified into two categories. Binary classification was implemented by the support vector machine and the decision tree, and receiver operating characteristic (ROC) curves were obtained and plotted to analyze the performance of the proposed algorithm. The experimental results revealed that the generic overall quality classification achieved a sensitivity of 87.45% at a specificity of 91.66%, with an area under the ROC curve of 0.9452, indicating the value of applying the algorithm, which is based on the human vision system, to assess the image quality of non-mydriatic photography, especially for low-cost ophthalmological telemedicine applications.

Ringing reduced iterative deconvolution for astronomical optical image using gradient constraint regularization

It is difficult to restore images with details preserving and ringing suppressing. A gradient minimization based image restoration method is proposed for astronomical imagery. We consider no prior knowledge of noise statistics for image deconvolution, meanwhile, L0 gradient measure is also treated as the regularization term to reduce ringing artifacts. According to experiments of real image, the proposed algorithm could produce a high-quality result with ringing suppression. Comparing with other algorithms via visual effect and image quality assessment, the proposed algorithm performs best in balancing details restoration and ringing reduction.

Accelerated motion corrected three-dimensional abdominal MRI using total variation regularized SENSE reconstruction.

PurposeDevelop a nonrigid motion corrected reconstruction for highly accelerated free‐breathing three‐dimensional (3D) abdominal images without external sensors or additional scans.MethodsThe proposed method accelerates the acquisition by undersampling and performs motion correction directly in the reconstruction using a general matrix description of the acquisition. Data are acquired using a self‐gated 3D golden radial phase encoding trajectory, enabling a two stage reconstruction to estimate and then correct motion of the same data. In the first stage total variation regularized iterative SENSE is used to reconstruct highly undersampled respiratory resolved images. A nonrigid registration of these images is performed to estimate the complex motion in the abdomen. In the second stage, the estimated motion fields are incorporated in a general matrix reconstruction, which uses total variation regularization and incorporates k‐space data from multiple respiratory positions. The proposed approach was tested on nine healthy volunteers and compared against a standard gated reconstruction using measures of liver sharpness, gradient entropy, visual assessment of image sharpness and overall image quality by two experts.ResultsThe proposed method achieves similar quality to the gated reconstruction with nonsignificant differences for liver sharpness (1.18 and 1.00, respectively), gradient entropy (1.00 and 1.00), visual score of image sharpness (2.22 and 2.44), and visual rank of image quality (3.33 and 3.39). An average reduction of the acquisition time from 102 s to 39 s could be achieved with the proposed method.ConclusionIn vivo results demonstrate the feasibility of the proposed method showing similar image quality to the standard gated reconstruction while using data corresponding to a significantly reduced acquisition time. Magn Reson Med, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Magn Reson Med 75:1484–1498, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.

Adaptive Total Variation Regularization Based SAR Image Despeckling and Despeckling Evaluation Index

We introduce a total variation (TV) regularization model for synthetic aperture radar (SAR) image despeckling. A dual-formulation-based adaptive TV (ATV) regularization method is applied to solve the TV regularization. The parameter adaptation of the TV regularization is performed based on the noise level estimated via wavelets. The TV-regularization-based image restoration model has a good performance in preserving image sharpness and edges while removing noises, and it is therefore effective for edge preserve SAR image despeckling. Experiments have been carried out using optical images contaminated with artificial speckles first and then SAR images. A despeckling evaluation index (DEI) is designed to assess the effectiveness of edge preserve despeckling on SAR images, which is based on the ratio of the standard deviations of two neighborhood areas of different sizes of a pixel. Experimental results show that the proposed ATV method can effectively suppress SAR image speckles without compromising the edge sharpness of image features according to both subjective visual assessment of image quality and objective evaluation using DEI.

Characterization of parallel-hole collimator using Monte Carlo Simulation.

Objective:Accuracy of in vivo activity quantification improves after the correction of penetrated and scattered photons. However, accurate assessment is not possible with physical experiment. We have used Monte Carlo Simulation to accurately assess the contribution of penetrated and scattered photons in the photopeak window.Materials and Methods:Simulations were performed with Simulation of Imaging Nuclear Detectors Monte Carlo Code. The simulations were set up in such a way that it provides geometric, penetration, and scatter components after each simulation and writes binary images to a data file. These components were analyzed graphically using Microsoft Excel (Microsoft Corporation, USA). Each binary image was imported in software (ImageJ) and logarithmic transformation was applied for visual assessment of image quality, plotting profile across the center of the images and calculating full width at half maximum (FWHM) in horizontal and vertical directions.Results:The geometric, penetration, and scatter at 140 keV for low-energy general-purpose were 93.20%, 4.13%, 2.67% respectively. Similarly, geometric, penetration, and scatter at 140 keV for low-energy high-resolution (LEHR), medium-energy general-purpose (MEGP), and high-energy general-purpose (HEGP) collimator were (94.06%, 3.39%, 2.55%), (96.42%, 1.52%, 2.06%), and (96.70%, 1.45%, 1.85%), respectively. For MEGP collimator at 245 keV photon and for HEGP collimator at 364 keV were 89.10%, 7.08%, 3.82% and 67.78%, 18.63%, 13.59%, respectively.Conclusion:Low-energy general-purpose and LEHR collimator is best to image 140 keV photon. HEGP can be used for 245 keV and 364 keV; however, correction for penetration and scatter must be applied if one is interested to quantify the in vivo activity of energy 364 keV. Due to heavy penetration and scattering, 511 keV photons should not be imaged with HEGP collimator.

Despeckle Filtering for Multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) Texture Analysis of Ultrasound Images of the Intima-Media Complex.

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). Typically, the IMT grows with age and this is used as a sign of increased risk of CVD. Beyond thickness, there is also clinical interest in identifying how the composition and texture of the intima-media complex (IMC) changed and how these textural changes grow into atherosclerotic plaques that can cause stroke. Clearly though texture analysis of ultrasound images can be greatly affected by speckle noise, our goal here is to develop effective despeckle noise methods that can recover image texture associated with increased rates of atherosclerosis disease. In this study, we perform a comparative evaluation of several despeckle filtering methods, on 100 ultrasound images of the CCA, based on the extracted multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) texture features and visual image quality assessment by two clinical experts. Texture features were extracted from the automatically segmented IMC for three different age groups. The despeckle filters hybrid median and the homogeneous mask area filter showed the best performance by improving the class separation between the three age groups and also yielded significantly improved image quality.

A web-based digital analysis interface for image quality assessment

Image processing and transmission systems may introduce some amount of distortion or artefacts in a digital image. This fact usually leads to a visual or statistical image quality assessment (IQA) required in many applications and research studies in order to analyse a product image in terms of deteriorations as well as effects of the processing. There are numerous IQA criteria presented in the literature separately that makes it really difficult both for use in comparative analyses and for educational purposes. In this presented work, a user friendly web-based digital educational interface for full-reference or no-reference image quality assessment using MATLAB builder NE has been developed. In addition to this, developed system performs user-defined optional deteriorations (median noise, Gaussian blur, motion blur, high-pass filter and jpeg compression) on the image and assesses deterioration of the image. It is an extremely easy, fast and economical way of analysing digital images, especially designed for researchers, graduate and postgraduate students who work on digital image processing. Using this web-based tool well contributes to teaching all of the IQA methods and quality effects of systematic distortions on the image as well as establishes a scientific benchmark for researchers.

Characterization of a constrained paired‐view technique in iterative reconstruction for breast tomosynthesis

The order in which the projection views are employed in the reconstruction of tomosynthesis by iterative algorithms, such as simultaneous algebraic reconstruction technique and maximum likelihood, has a strong effect on the rate of convergence, accuracy, and the edge-blurring artifacts in the reconstructed image. The purpose of this investigation was to characterize and evaluate the effects of ordering schemes on image quality for breast tomosynthesis reconstruction and to explore a new constrained paired-view technique that could provide reduction of reconstruction artifacts. In this work, the authors compared several different ordering schemes and characterized the image quality and the formation of out-of-plane artifacts. Furthermore, a new normalization method is presented. It produces more accurate reconstructions with reduced artifacts comparing to the standard method of sequential ordering. In addition to visual assessment of image quality, several indices such as the signal-difference-to-noise ratio, the artifact-spread function, and the lesion detectability (d(')) were computed to quantitatively evaluate the effect of ordering scheme. The sets of breast tomosynthesis projection images were simulated for reconstruction; one set had uniform background (white noise only) and the other two contained both anatomic background and quantum noise. Clinical breast images were also studied for comparison. The authors have quantified the image quality in reconstructed slices for a range of tumor sizes. The authors' proposed method provides better performance for all of the metrics tested (contrast, d('), and the level of artifacts) both for the uniform phantom case and in the presence of anatomical structure. The paired projection normalization provides better performance in the image quality of the reconstructed slices, and results in a lower level of artifacts in the Z direction. This implies that even a relatively simple method like the "side-to-side" sequence, which pairs two symmetrical projections with equal angular distance from the central projection, would achieve better reconstructed image quality than the conventional "step-by-step" method, which uses sequential projections one after another.

Image Sharpness Assessment Based on Local Phase Coherence

Sharpness is an important determinant in visual assessment of image quality. The human visual system is able to effortlessly detect blur and evaluate sharpness of visual images, but the underlying mechanism is not fully understood. Existing blur/sharpness evaluation algorithms are mostly based on edge width, local gradient, or energy reduction of global/local high frequency content. Here we understand the subject from a different perspective, where sharpness is identified as strong local phase coherence (LPC) near distinctive image features evaluated in the complex wavelet transform domain. Previous LPC computation is restricted to be applied to complex coefficients spread in three consecutive dyadic scales in the scale-space. Here we propose a flexible framework that allows for LPC computation in arbitrary fractional scales. We then develop a new sharpness assessment algorithm without referencing the original image. We use four subject-rated publicly available image databases to test the proposed algorithm, which demonstrates competitive performance when compared with state-of-the-art algorithms.

Comparison of clinical and physics scoring of PET images when image reconstruction parametersare varied

In this study the quantitative and qualitative image quality (IQ) measurements with clinical judgement of IQ in positron emission tomography (PET) were compared. The limitations of IQ metrics and the proposed criteria of acceptability for PET scanners are discussed. Phantom and patient images were reconstructed using seven different iterative reconstruction protocols. For each reconstructed set of images, IQ was scored based both on the visual analysis and on the quantitative metrics. The quantitative physics metrics did not rank the reconstruction protocols in the same order as the clinicians' scoring of perceived IQ (R(s)=-0.54). Better agreement was achieved when comparing the clinical perception of IQ to the physicist's visual assessment of IQ in the phantom images (R(s)=+0.59). The closest agreement was seen between the quantitative physics metrics and the measurement of the standard uptake values (SUVs) in small tumours (R(s)=+0.92). Given the disparity between the clinical perception of IQ and the physics metrics a cautious approach to use of IQ measurements for determining suspension levels is warranted.

Quantification of image quality using information theory

Aims of present study were to examine usefulness of information theory in visual assessment of image quality. We applied first order approximation of the Shannon's information theory to compute information losses (IL). Images of a contrast-detail mammography (CDMAM) phantom were acquired with computed radiographies for various radiation doses. Information content was defined as the entropy Σp( i )log(1/p ( i )), in which detection probabilities p ( i ) were calculated from distribution of detection rate of the CDMAM. IL was defined as the difference between information content and information obtained. IL decreased with increases in the disk diameters (P < 0.0001, ANOVA) and in the radiation doses (P < 0.002, F-test). Sums of IL, which we call total information losses (TIL), were closely correlated with the image quality figures (r = 0.985). TIL was dependent on the distribution of image reading ability of each examinee, even when average reading ratio was the same in the group. TIL was shown to be sensitive to the observers' distribution of image readings and was expected to improve the evaluation of image quality.

Cone-beam artifact evaluation of the factorization method

The authors investigate the CB artifact behavior of the factorization approach recently suggested for image reconstruction in circular cone-beam computed tomography. This investigation is carried out in a typical C-arm geometry and involves simulated data and for the first time also phantom and clinical CB data acquired with a commercially available angiographic system. The CB artifact level is first measured using quantitative figures-of-merit that are computed from the reconstructions of the mathematical FORBILD head phantom and of a modified disk phantom. The authors then show reconstructions from a physical thorax phantom and clinical head data sets for a visual assessment of image quality. The performance of the factorization method is primarily compared to that of short-scan FDK, but the authors also show the results obtained with the full-scan FDK and the virtual PI-line BPF method for the simulation studies, as a benchmark. Quantitatively, the FORBILD head phantom reconstructions of both FDK methods show a spatially averaged bias of up to 1.2% in the axial slices about 9 cm away from the plane of the scan, which is placed 4 cm below the central slice through the phantom. The artifact level for the short-scan FDK method and the virtual PI-line BPF method noticeably depends on the scan orientation. The factorization approach can significantly reduce both, this dependency as well as the reconstruction bias. It also shows visually an improved quality of the clinical images compared to short-scan FDK, particularly close to the spine and in the subcranial regions of the clinical data sets. The factorization approach comes with noticeably lower reconstruction bias than the FDK methods and is least sensitive to the scan orientation among all considered short-scan methods. The data inconsistencies contained in the real data sets, such as scatter, beam hardening, or data truncation, show only little impact on the factorization results. Hence, in both, reconstructions from real and simulated data, the factorization method yields better image quality than short-scan FDK, albeit at the cost of some slight, directed high-frequency artifacts that are mostly visible in axial slices.

ＦＤＧ−ＰＥＴ／ＣＴ検査における物理学的指標に基づいた収集時間の最適化

The image quality of Positron Emission Tomography (PET) using (18)F-fluoro-2-deoxy-D-glucose is extremely important to diagnose cancer precisely. The purpose of this study is to inspect the physical indexes that are correlated with image quality and optimization of the scan time, utilizing the physical index. This study calculated two kinds of patient noise equivalent counts (NEC(patient) and NEC(density)) and signal to noise ratio in liver (SNR(liver)) to measure PET image quality. We estimated the correlation coefficient between the visual assessment of PET image quality and physical indexes to assess the degree of correlation. We also set the optimal scan time, depending on body mass index (BMI), using the physical index and examined the efficacy of the optimization. NEC(density) showed the highest correlation coefficient in PET image quality (r=0.743, p<0.001). By optimizing the scan time using NEC(density), we showed there was no correlation between BMI and NEC(density) (r=0.192, p=0.047). In addition, reduced dependence of the PET image quality by BMI was showed. The optimization of the scan time using NEC(density) reduces deterioration of the PET image quality by patient habitus.

Micro-computed tomography of pulmonary fibrosis in mice induced by adenoviral gene transfer of biologically active transforming growth factor-β1

BackgroundMicro-computed tomography (micro-CT) is a novel tool for monitoring acute and chronic disease states in small laboratory animals. Its value for assessing progressive lung fibrosis in mice has not been reported so far. Here we examined the importance of in vivo micro-CT as non-invasive tool to assess progression of pulmonary fibrosis in mice over time.MethodsPulmonary fibrosis was induced in mice by intratracheal delivery of an adenoviral gene vector encoding biologically active TGF-ß1 (AdTGF-ß1). Respiratory gated and ungated micro-CT scans were performed at 1, 2, 3, and 4 weeks post pulmonary adenoviral gene or control vector delivery, and were then correlated with respective histopathology-based Ashcroft scoring of pulmonary fibrosis in mice. Visual assessment of image quality and consolidation was performed by 3 observers and a semi-automated quantification algorithm was applied to quantify aerated pulmonary volume as an inverse surrogate marker for pulmonary fibrosis.ResultsWe found a significant correlation between classical Ashcroft scoring and micro-CT assessment using both visual assessment and the semi-automated quantification algorithm. Pulmonary fibrosis could be clearly detected in micro-CT, image quality values were higher for respiratory gated exams, although differences were not significant. For assessment of fibrosis no significant difference between respiratory gated and ungated exams was observed.ConclusionsTogether, we show that micro-CT is a powerful tool to assess pulmonary fibrosis in mice, using both visual assessment and semi-automated quantification algorithms. These data may be important in view of pre-clinical pharmacologic interventions for the treatment of lung fibrosis in small laboratory animals.