Achieving Quality Integrated Education.

ERIC Educational Resources Information Center

Hawley, Willis D.; Rosenholtz, Susan J.

While desegregation is neither a necessary nor a sufficient condition for ensuring either equity or quality education for minorities, the evidence is convincing that it is "educationally more difficult" to improve student achievement in segregated schools. Desegregation offers the opportunity to enhance the quality of education, particularly when…

Social image quality

NASA Astrophysics Data System (ADS)

Qiu, Guoping; Kheiri, Ahmed

2011-01-01

Current subjective image quality assessments have been developed in the laboratory environments, under controlledconditions, and are dependent on the participation of limited numbers of observers. In this research, with the help of Web 2.0 and social media technology, a new method for building a subjective image quality metric has been developed where the observers are the Internet users. A website with a simple user interface that enables Internet users from anywhere at any time to vote for a better quality version of a pair of the same image has been constructed. Users' votes are recorded and used to rank the images according to their perceived visual qualities. We have developed three rank aggregation algorithms to process the recorded pair comparison data, the first uses a naive approach, the second employs a Condorcet method, and the third uses the Dykstra's extension of Bradley-Terry method. The website has been collecting data for about three months and has accumulated over 10,000 votes at the time of writing this paper. Results show that the Internet and its allied technologies such as crowdsourcing offer a promising new paradigm for image and video quality assessment where hundreds of thousands of Internet users can contribute to building more robust image quality metrics. We have made Internet user generated social image quality (SIQ) data of a public image database available online (http://www.hdri.cs.nott.ac.uk/siq/) to provide the image quality research community with a new source of ground truth data. The website continues to collect votes and will include more public image databases and will also be extended to include videos to collect social video quality (SVQ) data. All data will be public available on the website in due course.

Dose reduction of up to 89% while maintaining image quality in cardiovascular CT achieved with prospective ECG gating

NASA Astrophysics Data System (ADS)

Londt, John H.; Shreter, Uri; Vass, Melissa; Hsieh, Jiang; Ge, Zhanyu; Adda, Olivier; Dowe, David A.; Sabllayrolles, Jean-Louis

2007-03-01

We present the results of dose and image quality performance evaluation of a novel, prospective ECG-gated Coronary CT Angiography acquisition mode (SnapShot Pulse, LightSpeed VCT-XT scanner, GE Healthcare, Waukesha, WI), and compare it to conventional retrospective ECG gated helical acquisition in clinical and phantom studies. Image quality phantoms were used to measure noise, slice sensitivity profile, in-plane resolution, low contrast detectability and dose, using the two acquisition modes. Clinical image quality and diagnostic confidence were evaluated in a study of 31 patients scanned with the two acquisition modes. Radiation dose reduction in clinical practice was evaluated by tracking 120 consecutive patients scanned with the prospectively gated scan mode. In the phantom measurements, the prospectively gated mode resulted in equivalent or better image quality measures at dose reductions of up to 89% compared to non-ECG modulated conventional helical scans. In the clinical study, image quality was rated excellent by expert radiologist reviewing the cases, with pathology being identical using the two acquisition modes. The average dose to patients in the clinical practice study was 5.6 mSv, representing 50% reduction compared to a similar patient population scanned with the conventional helical mode.

Achieving total quality through intelligence.

PubMed

Fuld, L M

1992-02-01

American firms want 'total quality'. The time and money spent by U.S. companies attempting to qualify for the coveted Baldrige Award exemplifies corporate America's desire to achieve new quality standards. Corporate intelligence and 'total quality' are inextricably linked. In this article, the authors demonstrate how shared and properly-used information can be a powerful tool for elevating quality standards, and how corporate intelligence programmes can provide the information links vital for success in attaining the highest standards of quality.

Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Dandan; Li, Houqiang

2017-12-01

Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

Paediatric cerebrovascular CT angiography-towards better image quality.

PubMed

Thust, Stefanie C; Chong, Wui Khean Kling; Gunny, Roxana; Mazumder, Asif; Poitelea, Marius; Welsh, Anna; Ederies, Ash; Mankad, Kshitij

2014-12-01

Paediatric cerebrovascular CT angiography (CTA) can be challenging to perform due to variable cardiovascular physiology between different age groups and the risk of movement artefact. This analysis aimed to determine what proportion of CTA at our institution was of diagnostic quality and identify technical factors which could be improved. a retrospective analysis of 20 cases was performed at a national paediatric neurovascular centre assessing image quality with a subjective scoring system and Hounsfield Unit (HU) measurements. Demographic data, contrast dose, flow rate and triggering times were recorded for each patient. Using a qualitative scoring system, 75% of studies were found to be of diagnostic quality (n=9 'good', n=6 'satisfactory') and 25% (n=5) were 'poor'. Those judged subjectively to be poor had arterial contrast density measured at less than 250 HU. Increased arterial opacification was achieved for cases performed with an increased flow rate (2.5-4 mL/s) and higher intravenous contrast dose (2 mL/kg). Triggering was found to be well timed in nine cases, early in four cases and late in seven cases. Of the scans triggered early, 75% were poor. Of the scans triggered late, less (29%) were poor. High flow rates (>2.5 mL/s) were a key factor for achieving high quality paediatric cerebrovascular CTA imaging. However, appropriate triggering by starting the scan immediately on contrast opacification of the monitoring vessel plays an important role and could maintain image quality when flow rates were lower. Early triggering appeared more detrimental than late.

PLÉIADES Project: Assessment of Georeferencing Accuracy, Image Quality, Pansharpening Performence and Dsm/dtm Quality

NASA Astrophysics Data System (ADS)

Topan, Hüseyin; Cam, Ali; Özendi, Mustafa; Oruç, Murat; Jacobsen, Karsten; Taşkanat, Talha

2016-06-01

Pléiades 1A and 1B are twin optical satellites of Optical and Radar Federated Earth Observation (ORFEO) program jointly running by France and Italy. They are the first satellites of Europe with sub-meter resolution. Airbus DS (formerly Astrium Geo) runs a MyGIC (formerly Pléiades Users Group) program to validate Pléiades images worldwide for various application purposes. The authors conduct three projects, one is within this program, the second is supported by BEU Scientific Research Project Program, and the third is supported by TÜBİTAK. Assessment of georeferencing accuracy, image quality, pansharpening performance and Digital Surface Model/Digital Terrain Model (DSM/DTM) quality subjects are investigated in these projects. For these purposes, triplet panchromatic (50 cm Ground Sampling Distance (GSD)) and VNIR (2 m GSD) Pléiades 1A images were investigated over Zonguldak test site (Turkey) which is urbanised, mountainous and covered by dense forest. The georeferencing accuracy was estimated with a standard deviation in X and Y (SX, SY) in the range of 0.45m by bias corrected Rational Polynomial Coefficient (RPC) orientation, using ~170 Ground Control Points (GCPs). 3D standard deviation of ±0.44m in X, ±0.51m in Y, and ±1.82m in Z directions have been reached in spite of the very narrow angle of convergence by bias corrected RPC orientation. The image quality was also investigated with respect to effective resolution, Signal to Noise Ratio (SNR) and blur coefficient. The effective resolution was estimated with factor slightly below 1.0, meaning that the image quality corresponds to the nominal resolution of 50cm. The blur coefficients were achieved between 0.39-0.46 for triplet panchromatic images, indicating a satisfying image quality. SNR is in the range of other comparable space borne images which may be caused by de-noising of Pléiades images. The pansharpened images were generated by various methods, and are validated by most common statistical

Digital mammography--DQE versus optimized image quality in clinical environment: an on site study

NASA Astrophysics Data System (ADS)

Oberhofer, Nadia; Fracchetti, Alessandro; Springeth, Margareth; Moroder, Ehrenfried

2010-04-01

The intrinsic quality of the detection system of 7 different digital mammography units (5 direct radiography DR; 2 computed radiography CR), expressed by DQE, has been compared with their image quality/dose performances in clinical use. DQE measurements followed IEC 62220-1-2 using a tungsten test object for MTF determination. For image quality assessment two different methods have been applied: 1) measurement of contrast to noise ratio (CNR) according to the European guidelines and 2) contrast-detail (CD) evaluation. The latter was carried out with the phantom CDMAM ver. 3.4 and the commercial software CDMAM Analyser ver. 1.1 (both Artinis) for automated image analysis. The overall image quality index IQFinv proposed by the software has been validated. Correspondence between the two methods has been shown figuring out a linear correlation between CNR and IQFinv. All systems were optimized with respect to image quality and average glandular dose (AGD) within the constraints of automatic exposure control (AEC). For each equipment, a good image quality level was defined by means of CD analysis, and the corresponding CNR value considered as target value. The goal was to achieve for different PMMA-phantom thicknesses constant image quality, that means the CNR target value, at minimum dose. All DR systems exhibited higher DQE and significantly better image quality compared to CR systems. Generally switching, where available, to a target/filter combination with an x-ray spectrum of higher mean energy permitted dose savings at equal image quality. However, several systems did not allow to modify the AEC in order to apply optimal radiographic technique in clinical use. The best ratio image quality/dose was achieved by a unit with a-Se detector and W anode only recently available on the market.

Paediatric cerebrovascular CT angiography—towards better image quality

PubMed Central

Thust, Stefanie C.; Chong, Wui Khean Kling; Gunny, Roxana; Mazumder, Asif; Poitelea, Marius; Welsh, Anna; Ederies, Ash

2014-01-01

Background Paediatric cerebrovascular CT angiography (CTA) can be challenging to perform due to variable cardiovascular physiology between different age groups and the risk of movement artefact. This analysis aimed to determine what proportion of CTA at our institution was of diagnostic quality and identify technical factors which could be improved. Materials and methods a retrospective analysis of 20 cases was performed at a national paediatric neurovascular centre assessing image quality with a subjective scoring system and Hounsfield Unit (HU) measurements. Demographic data, contrast dose, flow rate and triggering times were recorded for each patient. Results Using a qualitative scoring system, 75% of studies were found to be of diagnostic quality (n=9 ‘good’, n=6 ‘satisfactory’) and 25% (n=5) were ‘poor’. Those judged subjectively to be poor had arterial contrast density measured at less than 250 HU. Increased arterial opacification was achieved for cases performed with an increased flow rate (2.5-4 mL/s) and higher intravenous contrast dose (2 mL/kg). Triggering was found to be well timed in nine cases, early in four cases and late in seven cases. Of the scans triggered early, 75% were poor. Of the scans triggered late, less (29%) were poor. Conclusions High flow rates (>2.5 mL/s) were a key factor for achieving high quality paediatric cerebrovascular CTA imaging. However, appropriate triggering by starting the scan immediately on contrast opacification of the monitoring vessel plays an important role and could maintain image quality when flow rates were lower. Early triggering appeared more detrimental than late. PMID:25525579

Image quality assessment metric for frame accumulated image

NASA Astrophysics Data System (ADS)

Yu, Jianping; Li, Gang; Wang, Shaohui; Lin, Ling

2018-01-01

The medical image quality determines the accuracy of diagnosis, and the gray-scale resolution is an important parameter to measure image quality. But current objective metrics are not very suitable for assessing medical images obtained by frame accumulation technology. Little attention was paid to the gray-scale resolution, basically based on spatial resolution and limited to the 256 level gray scale of the existing display device. Thus, this paper proposes a metric, "mean signal-to-noise ratio" (MSNR) based on signal-to-noise in order to be more reasonable to evaluate frame accumulated medical image quality. We demonstrate its potential application through a series of images under a constant illumination signal. Here, the mean image of enough images was regarded as the reference image. Several groups of images by different frame accumulation and their MSNR were calculated. The results of the experiment show that, compared with other quality assessment methods, the metric is simpler, more effective, and more suitable for assessing frame accumulated images that surpass the gray scale and precision of the original image.

Paediatric x-ray radiation dose reduction and image quality analysis.

PubMed

Martin, L; Ruddlesden, R; Makepeace, C; Robinson, L; Mistry, T; Starritt, H

2013-09-01

Collaboration of multiple staff groups has resulted in significant reduction in the risk of radiation-induced cancer from radiographic x-ray exposure during childhood. In this study at an acute NHS hospital trust, a preliminary audit identified initial exposure factors. These were compared with European and UK guidance, leading to the introduction of new factors that were in compliance with European guidance on x-ray tube potentials. Image quality was assessed using standard anatomical criteria scoring, and visual grading characteristics analysis assessed the impact on image quality of changes in exposure factors. This analysis determined the acceptability of gradual radiation dose reduction below the European and UK guidance levels. Chest and pelvis exposures were optimised, achieving dose reduction for each age group, with 7%-55% decrease in critical organ dose. Clinicians confirmed diagnostic image quality throughout the iterative process. Analysis of images acquired with preliminary and final exposure factors indicated an average visual grading analysis result of 0.5, demonstrating equivalent image quality. The optimisation process and final radiation doses are reported for Carestream computed radiography to aid other hospitals in minimising radiation risks to children.

Image quality (IQ) guided multispectral image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Chen, Genshe; Wang, Zhonghai; Blasch, Erik

2016-05-01

Image compression is necessary for data transportation, which saves both transferring time and storage space. In this paper, we focus on our discussion on lossy compression. There are many standard image formats and corresponding compression algorithms, for examples, JPEG (DCT -- discrete cosine transform), JPEG 2000 (DWT -- discrete wavelet transform), BPG (better portable graphics) and TIFF (LZW -- Lempel-Ziv-Welch). The image quality (IQ) of decompressed image will be measured by numerical metrics such as root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural Similarity (SSIM) Index. Given an image and a specified IQ, we will investigate how to select a compression method and its parameters to achieve an expected compression. Our scenario consists of 3 steps. The first step is to compress a set of interested images by varying parameters and compute their IQs for each compression method. The second step is to create several regression models per compression method after analyzing the IQ-measurement versus compression-parameter from a number of compressed images. The third step is to compress the given image with the specified IQ using the selected compression method (JPEG, JPEG2000, BPG, or TIFF) according to the regressed models. The IQ may be specified by a compression ratio (e.g., 100), then we will select the compression method of the highest IQ (SSIM, or PSNR). Or the IQ may be specified by a IQ metric (e.g., SSIM = 0.8, or PSNR = 50), then we will select the compression method of the highest compression ratio. Our experiments tested on thermal (long-wave infrared) images (in gray scales) showed very promising results.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies.

PubMed

Welikala, R A; Fraz, M M; Foster, P J; Whincup, P H; Rudnicka, A R; Owen, C G; Strachan, D P; Barman, S A

2016-04-01

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost. Copyright © 2016 Elsevier Ltd. All rights reserved.

Perceptual quality prediction on authentically distorted images using a bag of features approach

PubMed Central

Ghadiyaram, Deepti; Bovik, Alan C.

2017-01-01

Current top-performing blind perceptual image quality prediction models are generally trained on legacy databases of human quality opinion scores on synthetically distorted images. Therefore, they learn image features that effectively predict human visual quality judgments of inauthentic and usually isolated (single) distortions. However, real-world images usually contain complex composite mixtures of multiple distortions. We study the perceptually relevant natural scene statistics of such authentically distorted images in different color spaces and transform domains. We propose a “bag of feature maps” approach that avoids assumptions about the type of distortion(s) contained in an image and instead focuses on capturing consistencies—or departures therefrom—of the statistics of real-world images. Using a large database of authentically distorted images, human opinions of them, and bags of features computed on them, we train a regressor to conduct image quality prediction. We demonstrate the competence of the features toward improving automatic perceptual quality prediction by testing a learned algorithm using them on a benchmark legacy database as well as on a newly introduced distortion-realistic resource called the LIVE In the Wild Image Quality Challenge Database. We extensively evaluate the perceptual quality prediction model and algorithm and show that it is able to achieve good-quality prediction power that is better than other leading models. PMID:28129417

Image quality improvement in MDCT cardiac imaging via SMART-RECON method

NASA Astrophysics Data System (ADS)

Li, Yinsheng; Cao, Ximiao; Xing, Zhanfeng; Sun, Xuguang; Hsieh, Jiang; Chen, Guang-Hong

2017-03-01

Coronary CT angiography (CCTA) is a challenging imaging task currently limited by the achievable temporal resolution of modern Multi-Detector CT (MDCT) scanners. In this paper, the recently proposed SMARTRECON method has been applied in MDCT-based CCTA imaging to improve the image quality without any prior knowledge of cardiac motion. After the prospective ECG-gated data acquisition from a short-scan angular span, the acquired data were sorted into several sub-sectors of view angles; each corresponds to a 1/4th of the short-scan angular range. Information of the cardiac motion was thus encoded into the data in each view angle sub-sector. The SMART-RECON algorithm was then applied to jointly reconstruct several image volumes, each of which is temporally consistent with the data acquired in the corresponding view angle sub-sector. Extensive numerical simulations were performed to validate the proposed technique and investigate the performance dependence.

Impact of contact lens zone geometry and ocular optics on bifocal retinal image quality

PubMed Central

Bradley, Arthur; Nam, Jayoung; Xu, Renfeng; Harman, Leslie; Thibos, Larry

2014-01-01

Purpose To examine the separate and combined influences of zone geometry, pupil size, diffraction, apodisation and spherical aberration on the optical performance of concentric zonal bifocals. Methods Zonal bifocal pupil functions representing eye + ophthalmic correction were defined by interleaving wavefronts from separate optical zones of the bifocal. A two-zone design (a central circular inner zone surrounded by an annular outer-zone which is bounded by the pupil) and a five-zone design (a central small circular zone surrounded by four concentric annuli) were configured with programmable zone geometry, wavefront phase and pupil transmission characteristics. Using computational methods, we examined the effects of diffraction, Stiles Crawford apodisation, pupil size and spherical aberration on optical transfer functions for different target distances. Results Apodisation alters the relative weighting of each zone, and thus the balance of near and distance optical quality. When spherical aberration is included, the effective distance correction, add power and image quality depend on zone-geometry and Stiles Crawford Effect apodisation. When the outer zone width is narrow, diffraction limits the available image contrast when focused, but as pupil dilates and outer zone width increases, aberrations will limit the best achievable image quality. With two-zone designs, balancing near and distance image quality is not achieved with equal area inner and outer zones. With significant levels of spherical aberration, multi-zone designs effectively become multifocals. Conclusion Wave optics and pupil varying ocular optics significantly affect the imaging capabilities of different optical zones of concentric bifocals. With two-zone bifocal designs, diffraction, pupil apodisation spherical aberration, and zone size influence both the effective add power and the pupil size required to balance near and distance image quality. Five-zone bifocal designs achieve a high degree of

A quality quantitative method of silicon direct bonding based on wavelet image analysis

NASA Astrophysics Data System (ADS)

Tan, Xiao; Tao, Zhi; Li, Haiwang; Xu, Tiantong; Yu, Mingxing

2018-04-01

The rapid development of MEMS (micro-electro-mechanical systems) has received significant attention from researchers in various fields and subjects. In particular, the MEMS fabrication process is elaborate and, as such, has been the focus of extensive research inquiries. However, in MEMS fabrication, component bonding is difficult to achieve and requires a complex approach. Thus, improvements in bonding quality are relatively important objectives. A higher quality bond can only be achieved with improved measurement and testing capabilities. In particular, the traditional testing methods mainly include infrared testing, tensile testing, and strength testing, despite the fact that using these methods to measure bond quality often results in low efficiency or destructive analysis. Therefore, this paper focuses on the development of a precise, nondestructive visual testing method based on wavelet image analysis that is shown to be highly effective in practice. The process of wavelet image analysis includes wavelet image denoising, wavelet image enhancement, and contrast enhancement, and as an end result, can display an image with low background noise. In addition, because the wavelet analysis software was developed with MATLAB, it can reveal the bonding boundaries and bonding rates to precisely indicate the bond quality at all locations on the wafer. This work also presents a set of orthogonal experiments that consist of three prebonding factors, the prebonding temperature, the positive pressure value and the prebonding time, which are used to analyze the prebonding quality. This method was used to quantify the quality of silicon-to-silicon wafer bonding, yielding standard treatment quantities that could be practical for large-scale use.

Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion

PubMed Central

Tarolli, Jay G.; Jackson, Lauren M.; Winograd, Nicholas

2014-01-01

The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images, but also by detection sensitivity. As the probe size is reduced to below 1 µm, for example, a low signal in each pixel limits lateral resolution due to counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure. PMID:24912432

Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion

NASA Astrophysics Data System (ADS)

Tarolli, Jay G.; Jackson, Lauren M.; Winograd, Nicholas

2014-12-01

The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images but also by detection sensitivity. As the probe size is reduced to below 1 μm, for example, a low signal in each pixel limits lateral resolution because of counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure.

Improving image quality in laboratory x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

De Marco, F.; Marschner, M.; Birnbacher, L.; Viermetz, M.; Noël, P.; Herzen, J.; Pfeiffer, F.

2017-03-01

Grating-based X-ray phase-contrast (gbPC) is known to provide significant benefits for biomedical imaging. To investigate these benefits, a high-sensitivity gbPC micro-CT setup for small (≍ 5 cm) biological samples has been constructed. Unfortunately, high differential-phase sensitivity leads to an increased magnitude of data processing artifacts, limiting the quality of tomographic reconstructions. Most importantly, processing of phase-stepping data with incorrect stepping positions can introduce artifacts resembling Moiré fringes to the projections. Additionally, the focal spot size of the X-ray source limits resolution of tomograms. Here we present a set of algorithms to minimize artifacts, increase resolution and improve visual impression of projections and tomograms from the examined setup. We assessed two algorithms for artifact reduction: Firstly, a correction algorithm exploiting correlations of the artifacts and differential-phase data was developed and tested. Artifacts were reliably removed without compromising image data. Secondly, we implemented a new algorithm for flatfield selection, which was shown to exclude flat-fields with strong artifacts. Both procedures successfully improved image quality of projections and tomograms. Deconvolution of all projections of a CT scan can minimize blurring introduced by the finite size of the X-ray source focal spot. Application of the Richardson-Lucy deconvolution algorithm to gbPC-CT projections resulted in an improved resolution of phase-contrast tomograms. Additionally, we found that nearest-neighbor interpolation of projections can improve the visual impression of very small features in phase-contrast tomograms. In conclusion, we achieved an increase in image resolution and quality for the investigated setup, which may lead to an improved detection of very small sample features, thereby maximizing the setup's utility.

Full-reference quality assessment of stereoscopic images by learning binocular receptive field properties.

PubMed

Shao, Feng; Li, Kemeng; Lin, Weisi; Jiang, Gangyi; Yu, Mei; Dai, Qionghai

2015-10-01

Quality assessment of 3D images encounters more challenges than its 2D counterparts. Directly applying 2D image quality metrics is not the solution. In this paper, we propose a new full-reference quality assessment for stereoscopic images by learning binocular receptive field properties to be more in line with human visual perception. To be more specific, in the training phase, we learn a multiscale dictionary from the training database, so that the latent structure of images can be represented as a set of basis vectors. In the quality estimation phase, we compute sparse feature similarity index based on the estimated sparse coefficient vectors by considering their phase difference and amplitude difference, and compute global luminance similarity index by considering luminance changes. The final quality score is obtained by incorporating binocular combination based on sparse energy and sparse complexity. Experimental results on five public 3D image quality assessment databases demonstrate that in comparison with the most related existing methods, the devised algorithm achieves high consistency with subjective assessment.

JPEG2000 still image coding quality.

PubMed

Chen, Tzong-Jer; Lin, Sheng-Chieh; Lin, You-Chen; Cheng, Ren-Gui; Lin, Li-Hui; Wu, Wei

2013-10-01

This work demonstrates the image qualities between two popular JPEG2000 programs. Two medical image compression algorithms are both coded using JPEG2000, but they are different regarding the interface, convenience, speed of computation, and their characteristic options influenced by the encoder, quantization, tiling, etc. The differences in image quality and compression ratio are also affected by the modality and compression algorithm implementation. Do they provide the same quality? The qualities of compressed medical images from two image compression programs named Apollo and JJ2000 were evaluated extensively using objective metrics. These algorithms were applied to three medical image modalities at various compression ratios ranging from 10:1 to 100:1. Following that, the quality of the reconstructed images was evaluated using five objective metrics. The Spearman rank correlation coefficients were measured under every metric in the two programs. We found that JJ2000 and Apollo exhibited indistinguishable image quality for all images evaluated using the above five metrics (r > 0.98, p < 0.001). It can be concluded that the image quality of the JJ2000 and Apollo algorithms is statistically equivalent for medical image compression.

Process perspective on image quality evaluation

NASA Astrophysics Data System (ADS)

Leisti, Tuomas; Halonen, Raisa; Kokkonen, Anna; Weckman, Hanna; Mettänen, Marja; Lensu, Lasse; Ritala, Risto; Oittinen, Pirkko; Nyman, Göte

2008-01-01

The psychological complexity of multivariate image quality evaluation makes it difficult to develop general image quality metrics. Quality evaluation includes several mental processes and ignoring these processes and the use of a few test images can lead to biased results. By using a qualitative/quantitative (Interpretation Based Quality, IBQ) methodology, we examined the process of pair-wise comparison in a setting, where the quality of the images printed by laser printer on different paper grades was evaluated. Test image consisted of a picture of a table covered with several objects. Three other images were also used, photographs of a woman, cityscape and countryside. In addition to the pair-wise comparisons, observers (N=10) were interviewed about the subjective quality attributes they used in making their quality decisions. An examination of the individual pair-wise comparisons revealed serious inconsistencies in observers' evaluations on the test image content, but not on other contexts. The qualitative analysis showed that this inconsistency was due to the observers' focus of attention. The lack of easily recognizable context in the test image may have contributed to this inconsistency. To obtain reliable knowledge of the effect of image context or attention on subjective image quality, a qualitative methodology is needed.

Image quality scaling of electrophotographic prints

NASA Astrophysics Data System (ADS)

Johnson, Garrett M.; Patil, Rohit A.; Montag, Ethan D.; Fairchild, Mark D.

2003-12-01

Two psychophysical experiments were performed scaling overall image quality of black-and-white electrophotographic (EP) images. Six different printers were used to generate the images. There were six different scenes included in the experiment, representing photographs, business graphics, and test-targets. The two experiments were split into a paired-comparison experiment examining overall image quality, and a triad experiment judging overall similarity and dissimilarity of the printed images. The paired-comparison experiment was analyzed using Thurstone's Law, to generate an interval scale of quality, and with dual scaling, to determine the independent dimensions used for categorical scaling. The triad experiment was analyzed using multidimensional scaling to generate a psychological stimulus space. The psychophysical results indicated that the image quality was judged mainly along one dimension and that the relationships among the images can be described with a single dimension in most cases. Regression of various physical measurements of the images to the paired comparison results showed that a small number of physical attributes of the images could be correlated with the psychophysical scale of image quality. However, global image difference metrics did not correlate well with image quality.

TH-C-18A-06: Combined CT Image Quality and Radiation Dose Monitoring Program Based On Patient Data to Assess Consistency of Clinical Imaging Across Scanner Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christianson, O; Winslow, J; Samei, E

2014-06-15

Purpose: One of the principal challenges of clinical imaging is to achieve an ideal balance between image quality and radiation dose across multiple CT models. The number of scanners and protocols at large medical centers necessitates an automated quality assurance program to facilitate this objective. Therefore, the goal of this work was to implement an automated CT image quality and radiation dose monitoring program based on actual patient data and to use this program to assess consistency of protocols across CT scanner models. Methods: Patient CT scans are routed to a HIPPA compliant quality assurance server. CTDI, extracted using opticalmore » character recognition, and patient size, measured from the localizers, are used to calculate SSDE. A previously validated noise measurement algorithm determines the noise in uniform areas of the image across the scanned anatomy to generate a global noise level (GNL). Using this program, 2358 abdominopelvic scans acquired on three commercial CT scanners were analyzed. Median SSDE and GNL were compared across scanner models and trends in SSDE and GNL with patient size were used to determine the impact of differing automatic exposure control (AEC) algorithms. Results: There was a significant difference in both SSDE and GNL across scanner models (9–33% and 15–35% for SSDE and GNL, respectively). Adjusting all protocols to achieve the same image noise would reduce patient dose by 27–45% depending on scanner model. Additionally, differences in AEC methodologies across vendors resulted in disparate relationships of SSDE and GNL with patient size. Conclusion: The difference in noise across scanner models indicates that protocols are not optimally matched to achieve consistent image quality. Our results indicated substantial possibility for dose reduction while achieving more consistent image appearance. Finally, the difference in AEC methodologies suggests the need for size-specific CT protocols to minimize variability in

TU-EF-204-02: Hiigh Quality and Sub-MSv Cerebral CT Perfusion Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ke; Niu, Kai; Wu, Yijing

2015-06-15

Purpose: CT Perfusion (CTP) imaging is of great importance in acute ischemic stroke management due to its potential to detect hypoperfused yet salvageable tissue and distinguish it from definitely unsalvageable tissue. However, current CTP imaging suffers from poor image quality and high radiation dose (up to 5 mSv). The purpose of this work was to demonstrate that technical innovations such as Prior Image Constrained Compressed Sensing (PICCS) have the potential to address these challenges and achieve high quality and sub-mSv CTP imaging. Methods: (1) A spatial-temporal 4D cascaded system model was developed to indentify the bottlenecks in the current CTPmore » technology; (2) A task-based framework was developed to optimize the CTP system parameters; (3) Guided by (1) and (2), PICCS was customized for the reconstruction of CTP source images. Digital anthropomorphic perfusion phantoms, animal studies, and preliminary human subject studies were used to validate and evaluate the potentials of using these innovations to advance the CTP technology. Results: The 4D cascaded model was validated in both phantom and canine stroke models. Based upon this cascaded model, it has been discovered that, as long as the spatial resolution and noise properties of the 4D source CT images are given, the 3D MTF and NPS of the final CTP maps can be analytically derived for a given set of processing methods and parameters. The cascaded model analysis also identified that the most critical technical factor in CTP is how to acquire and reconstruct high quality source images; it has very little to do with the denoising techniques often used after parametric perfusion calculations. This explained why PICCS resulted in a five-fold dose reduction or substantial improvement in image quality. Conclusion: Technical innovations generated promising results towards achieving high quality and sub-mSv CTP imaging for reliable and safe assessment of acute ischemic strokes. K. Li, K. Niu, Y. Wu

Design of a practical model-observer-based image quality assessment method for CT imaging systems

NASA Astrophysics Data System (ADS)

Tseng, Hsin-Wu; Fan, Jiahua; Cao, Guangzhi; Kupinski, Matthew A.; Sainath, Paavana

2014-03-01

The channelized Hotelling observer (CHO) is a powerful method for quantitative image quality evaluations of CT systems and their image reconstruction algorithms. It has recently been used to validate the dose reduction capability of iterative image-reconstruction algorithms implemented on CT imaging systems. The use of the CHO for routine and frequent system evaluations is desirable both for quality assurance evaluations as well as further system optimizations. The use of channels substantially reduces the amount of data required to achieve accurate estimates of observer performance. However, the number of scans required is still large even with the use of channels. This work explores different data reduction schemes and designs a new approach that requires only a few CT scans of a phantom. For this work, the leave-one-out likelihood (LOOL) method developed by Hoffbeck and Landgrebe is studied as an efficient method of estimating the covariance matrices needed to compute CHO performance. Three different kinds of approaches are included in the study: a conventional CHO estimation technique with a large sample size, a conventional technique with fewer samples, and the new LOOL-based approach with fewer samples. The mean value and standard deviation of area under ROC curve (AUC) is estimated by shuffle method. Both simulation and real data results indicate that an 80% data reduction can be achieved without loss of accuracy. This data reduction makes the proposed approach a practical tool for routine CT system assessment.

A real time quality control application for animal production by image processing.

PubMed

Sungur, Cemil; Özkan, Halil

2015-11-01

Standards of hygiene and health are of major importance in food production, and quality control has become obligatory in this field. Thanks to rapidly developing technologies, it is now possible for automatic and safe quality control of food production. For this purpose, image-processing-based quality control systems used in industrial applications are being employed to analyze the quality of food products. In this study, quality control of chicken (Gallus domesticus) eggs was achieved using a real time image-processing technique. In order to execute the quality control processes, a conveying mechanism was used. Eggs passing on a conveyor belt were continuously photographed in real time by cameras located above the belt. The images obtained were processed by various methods and techniques. Using digital instrumentation, the volume of the eggs was measured, broken/cracked eggs were separated and dirty eggs were determined. In accordance with international standards for classifying the quality of eggs, the class of separated eggs was determined through a fuzzy implication model. According to tests carried out on thousands of eggs, a quality control process with an accuracy of 98% was possible. © 2014 Society of Chemical Industry.

Optimized Plane Wave Imaging for Fast and High-Quality Ultrasound Imaging.

PubMed

Jensen, Jonas; Stuart, Matthias Bo; Jensen, Jorgen Arendt

2016-11-01

This paper presents a method for optimizing parameters affecting the image quality in plane wave imaging. More specifically, the number of emissions and steering angles is optimized to attain the best images with the highest frame rate possible. The method is applied to a specific problem, where image quality for a λ -pitch transducer is compared with a λ /2-pitch transducer. Grating lobe artifacts for λ -pitch transducers degrade the contrast in plane wave images, and the impact on frame rate is studied. Field II simulations of plane wave images are made for all combinations of the parameters, and the optimal setup is selected based on Pareto optimality. The optimal setup for a simulated 4.1-MHz λ -pitch transducer uses 61 emissions and a maximum steering angle of 20° for depths from 0 to 60 mm. The achieved lateral full-width at half-maximum (FWHM) is 1.5λ and the contrast is -29 dB for a scatterer at 9 mm ( 24λ ). Using a λ /2-pitch transducer and only 21 emissions within the same angle range, the image quality is improved in terms of contrast, which is -37 dB. For imaging in regions deeper than 25 mm ( 66λ ), only 21 emissions are optimal for both the transducers, resulting in a -36 dB contrast at 34 mm ( 90λ ). Measurements are performed using the experimental SARUS scanner connected to a λ -pitch and λ /2-pitch transducer. A wire phantom and a tissue mimicking phantom containing anechoic cysts are scanned and show the performance using the optimized sequences for the transducers. FWHM is 1.6λ and contrast is -25 dB for a wire at 9 mm using the λ -pitch transducer. For the λ /2-pitch transducer, contrast is -29 dB. In vivo scans of the carotid artery of a healthy volunteer show improved contrast and present fewer artifacts, when using the λ /2-pitch transducer compared with the λ -pitch. It is demonstrated with a frame rate, which is three times higher for the λ /2-pitch transducer.

Characteristics of a New X-Ray Imaging System for Interventional Procedures: Improved Image Quality and Reduced Radiation Dose.

PubMed

Schernthaner, Ruediger E; Haroun, Reham R; Nguyen, Sonny; Duran, Rafael; Sohn, Jae Ho; Sahu, Sonia; Chapiro, Julius; Zhao, Yan; Radaelli, Alessandro; van der Bom, Imramsjah M; Mauti, Maria; Hong, Kelvin; Geschwind, Jean-François H; Lin, MingDe

2018-03-01

To compare image quality and radiation exposure between a new angiographic imaging system and the preceding generation system during uterine artery embolization (UAE). In this retrospective, IRB-approved two-arm study, 54 patients with symptomatic uterine fibroids were treated with UAE on two different angiographic imaging systems. The new system includes optimized acquisition parameters and real-time image processing algorithms. Air kerma (AK), dose area product (DAP) and acquisition time for digital fluoroscopy (DF) and digital subtraction angiography (DSA) were recorded. Body mass index was noted as well. DF image quality was assessed objectively by image noise measurements. DSA image quality was rated by two blinded, independent readers on a four-rank scale. Statistical differences were assessed with unpaired t tests and Wilcoxon rank-sum tests. There was no significant difference between the patients treated on the new (n = 36) and the old system (n = 18) regarding age (p = 0.10), BMI (p = 0.18), DF time (p = 0.35) and DSA time (p = 0.17). The new system significantly reduced the cumulative AK and DAP by 64 and 72%, respectively (median 0.58 Gy and 145.9 Gy*cm 2 vs. 1.62 Gy and 526.8 Gy*cm 2 , p < 0.01 for both). Specifically, DAP for DF and DSA decreased by 59% (75.3 vs. 181.9 Gy*cm 2 , p < 0.01) and 78% (67.6 vs. 312.2 Gy*cm 2 , p < 0.01), respectively. The new system achieved a significant decrease in DF image noise (p < 0.01) and a significantly better DSA image quality (p < 0.01). The new angiographic imaging system significantly improved image quality and reduced radiation exposure during UAE procedures.

Assessing product image quality for online shopping

NASA Astrophysics Data System (ADS)

Goswami, Anjan; Chung, Sung H.; Chittar, Naren; Islam, Atiq

2012-01-01

Assessing product-image quality is important in the context of online shopping. A high quality image that conveys more information about a product can boost the buyer's confidence and can get more attention. However, the notion of image quality for product-images is not the same as that in other domains. The perception of quality of product-images depends not only on various photographic quality features but also on various high level features such as clarity of the foreground or goodness of the background etc. In this paper, we define a notion of product-image quality based on various such features. We conduct a crowd-sourced experiment to collect user judgments on thousands of eBay's images. We formulate a multi-class classification problem for modeling image quality by classifying images into good, fair and poor quality based on the guided perceptual notions from the judges. We also conduct experiments with regression using average crowd-sourced human judgments as target. We compute a pseudo-regression score with expected average of predicted classes and also compute a score from the regression technique. We design many experiments with various sampling and voting schemes with crowd-sourced data and construct various experimental image quality models. Most of our models have reasonable accuracies (greater or equal to 70%) on test data set. We observe that our computed image quality score has a high (0.66) rank correlation with average votes from the crowd sourced human judgments.

Image Quality Ranking Method for Microscopy

PubMed Central

Koho, Sami; Fazeli, Elnaz; Eriksson, John E.; Hänninen, Pekka E.

2016-01-01

Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics. PMID:27364703

Comparative Analysis of Reconstructed Image Quality in a Simulated Chromotomographic Imager

DTIC Science & Technology

2014-03-01

quality . This example uses five basic images a backlit bar chart with random intensity, 100 nm separation. A total of 54 initial target...compared for a variety of scenes. Reconstructed image quality is highly dependent on the initial target hypercube so a total of 54 initial target...COMPARATIVE ANALYSIS OF RECONSTRUCTED IMAGE QUALITY IN A SIMULATED CHROMOTOMOGRAPHIC IMAGER THESIS

Automatic quality assessment of planetary images

NASA Astrophysics Data System (ADS)

Sidiropoulos, P.; Muller, J.-P.

2015-10-01

A significant fraction of planetary images are corrupted beyond the point that much scientific meaning can be extracted. For example, transmission errors result in missing data which is unrecoverable. The available planetary image datasets include many such "bad data", which both occupy valuable scientific storage resources and create false impressions about planetary image availability for specific planetary objects or target areas. In this work, we demonstrate a pipeline that we have developed to automatically assess the quality of planetary images. Additionally, this method discriminates between different types of image degradation, such as low-quality originating from camera flaws or low-quality triggered by atmospheric conditions, etc. Examples of quality assessment results for Viking Orbiter imagery will be also presented.

Guest Editorial Image Quality

NASA Astrophysics Data System (ADS)

Cheatham, Patrick S.

1982-02-01

The term image quality can, unfortunately, apply to anything from a public relations firm's discussion to a comparison between corner drugstores' film processing. If we narrow the discussion to optical systems, we clarify the problem somewhat, but only slightly. We are still faced with a multitude of image quality measures all different, and all couched in different terminology. Optical designers speak of MTF values, digital processors talk about summations of before and after image differences, pattern recognition engineers allude to correlation values, and radar imagers use side-lobe response values measured in decibels. Further complexity is introduced by terms such as information content, bandwidth, Strehl ratios, and, of course, limiting resolution. The problem is to compare these different yardsticks and try to establish some concrete ideas about evaluation of a final image. We need to establish the image attributes which are the most important to perception of the image in question and then begin to apply the different system parameters to those attributes.

NMF-Based Image Quality Assessment Using Extreme Learning Machine.

PubMed

Wang, Shuigen; Deng, Chenwei; Lin, Weisi; Huang, Guang-Bin; Zhao, Baojun

2017-01-01

Numerous state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage process: distortion description followed by distortion effects pooling. As for the first stage, the distortion descriptors or measurements are expected to be effective representatives of human visual variations, while the second stage should well express the relationship among quality descriptors and the perceptual visual quality. However, most of the existing quality descriptors (e.g., luminance, contrast, and gradient) do not seem to be consistent with human perception, and the effects pooling is often done in ad-hoc ways. In this paper, we propose a novel full-reference IQA metric. It applies non-negative matrix factorization (NMF) to measure image degradations by making use of the parts-based representation of NMF. On the other hand, a new machine learning technique [extreme learning machine (ELM)] is employed to address the limitations of the existing pooling techniques. Compared with neural networks and support vector regression, ELM can achieve higher learning accuracy with faster learning speed. Extensive experimental results demonstrate that the proposed metric has better performance and lower computational complexity in comparison with the relevant state-of-the-art approaches.

An Underwater Color Image Quality Evaluation Metric.

PubMed

Yang, Miao; Sowmya, Arcot

2015-12-01

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

Achieving Quality in Occupational Health

NASA Technical Reports Server (NTRS)

O'Donnell, Michele (Editor); Hoffler, G. Wyckliffe (Editor)

1997-01-01

The conference convened approximately 100 registered participants of invited guest speakers, NASA presenters, and a broad spectrum of the Occupational Health disciplines representing NASA Headquarters and all NASA Field Centers. Centered on the theme, "Achieving Quality in Occupational Health," conferees heard presentations from award winning occupational health program professionals within the Agency and from private industry; updates on ISO 9000 status, quality assurance, and information technologies; workshops on ergonomics and respiratory protection; an overview from the newly commissioned NASA Occupational Health Assessment Team; and a keynote speech on improving women's health. In addition, NASA occupational health specialists presented 24 poster sessions and oral deliveries on various aspects of current practice at their field centers.

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

Image quality and dose differences caused by vendor-specific image processing of neonatal radiographs.

PubMed

Sensakovic, William F; O'Dell, M Cody; Letter, Haley; Kohler, Nathan; Rop, Baiywo; Cook, Jane; Logsdon, Gregory; Varich, Laura

2016-10-01

Image processing plays an important role in optimizing image quality and radiation dose in projection radiography. Unfortunately commercial algorithms are black boxes that are often left at or near vendor default settings rather than being optimized. We hypothesize that different commercial image-processing systems, when left at or near default settings, create significant differences in image quality. We further hypothesize that image-quality differences can be exploited to produce images of equivalent quality but lower radiation dose. We used a portable radiography system to acquire images on a neonatal chest phantom and recorded the entrance surface air kerma (ESAK). We applied two image-processing systems (Optima XR220amx, by GE Healthcare, Waukesha, WI; and MUSICA(2) by Agfa HealthCare, Mortsel, Belgium) to the images. Seven observers (attending pediatric radiologists and radiology residents) independently assessed image quality using two methods: rating and matching. Image-quality ratings were independently assessed by each observer on a 10-point scale. Matching consisted of each observer matching GE-processed images and Agfa-processed images with equivalent image quality. A total of 210 rating tasks and 42 matching tasks were performed and effective dose was estimated. Median Agfa-processed image-quality ratings were higher than GE-processed ratings. Non-diagnostic ratings were seen over a wider range of doses for GE-processed images than for Agfa-processed images. During matching tasks, observers matched image quality between GE-processed images and Agfa-processed images acquired at a lower effective dose (11 ± 9 μSv; P < 0.0001). Image-processing methods significantly impact perceived image quality. These image-quality differences can be exploited to alter protocols and produce images of equivalent image quality but lower doses. Those purchasing projection radiography systems or third-party image-processing software should be aware that image

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Shiyu, E-mail: shiyu.xu@gmail.com; Chen, Ying, E-mail: adachen@siu.edu; Lu, Jianping

2015-09-15

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair basedmore » prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.« less

Automatic detection of retina disease: robustness to image quality and localization of anatomy structure.

PubMed

Karnowski, T P; Aykac, D; Giancardo, L; Li, Y; Nichols, T; Tobin, K W; Chaum, E

2011-01-01

The automated detection of diabetic retinopathy and other eye diseases in images of the retina has great promise as a low-cost method for broad-based screening. Many systems in the literature which perform automated detection include a quality estimation step and physiological feature detection, including the vascular tree and the optic nerve / macula location. In this work, we study the robustness of an automated disease detection method with respect to the accuracy of the optic nerve location and the quality of the images obtained as judged by a quality estimation algorithm. The detection algorithm features microaneurysm and exudate detection followed by feature extraction on the detected population to describe the overall retina image. Labeled images of retinas ground-truthed to disease states are used to train a supervised learning algorithm to identify the disease state of the retina image and exam set. Under the restrictions of high confidence optic nerve detections and good quality imagery, the system achieves a sensitivity and specificity of 94.8% and 78.7% with area-under-curve of 95.3%. Analysis of the effect of constraining quality and the distinction between mild non-proliferative diabetic retinopathy, normal retina images, and more severe disease states is included.

Image quality assessment using deep convolutional networks

NASA Astrophysics Data System (ADS)

Li, Yezhou; Ye, Xiang; Li, Yong

2017-12-01

This paper proposes a method of accurately assessing image quality without a reference image by using a deep convolutional neural network. Existing training based methods usually utilize a compact set of linear filters for learning features of images captured by different sensors to assess their quality. These methods may not be able to learn the semantic features that are intimately related with the features used in human subject assessment. Observing this drawback, this work proposes training a deep convolutional neural network (CNN) with labelled images for image quality assessment. The ReLU in the CNN allows non-linear transformations for extracting high-level image features, providing a more reliable assessment of image quality than linear filters. To enable the neural network to take images of any arbitrary size as input, the spatial pyramid pooling (SPP) is introduced connecting the top convolutional layer and the fully-connected layer. In addition, the SPP makes the CNN robust to object deformations to a certain extent. The proposed method taking an image as input carries out an end-to-end learning process, and outputs the quality of the image. It is tested on public datasets. Experimental results show that it outperforms existing methods by a large margin and can accurately assess the image quality on images taken by different sensors of varying sizes.

Image processing operations achievable with the Microchannel Spatial Light Modulator

NASA Astrophysics Data System (ADS)

Warde, C.; Fisher, A. D.; Thackara, J. I.; Weiss, A. M.

1980-01-01

The Microchannel Spatial Light Modulator (MSLM) is a versatile, optically-addressed, highly-sensitive device that is well suited for low-light-level, real-time, optical information processing. It consists of a photocathode, a microchannel plate (MCP), a planar acceleration grid, and an electro-optic plate in proximity focus. A framing rate of 20 Hz with full modulation depth, and 100 Hz with 20% modulation depth has been achieved in a vacuum-demountable LiTaO3 device. A halfwave exposure sensitivity of 2.2 mJ/sq cm and an optical information storage time of more than 2 months have been achieved in a similar gridless LiTaO3 device employing a visible photocathode. Image processing operations such as analog and digital thresholding, real-time image hard clipping, contrast reversal, contrast enhancement, image addition and subtraction, and binary-level logic operations such as AND, OR, XOR, and NOR can be achieved with this device. This collection of achievable image processing characteristics makes the MSLM potentially useful for a number of smart sensor applications.

The study of surgical image quality evaluation system by subjective quality factor method

NASA Astrophysics Data System (ADS)

Zhang, Jian J.; Xuan, Jason R.; Yang, Xirong; Yu, Honggang; Koullick, Edouard

2016-03-01

GreenLightTM procedure is an effective and economical way of treatment of benign prostate hyperplasia (BPH); there are almost a million of patients treated with GreenLightTM worldwide. During the surgical procedure, the surgeon or physician will rely on the monitoring video system to survey and confirm the surgical progress. There are a few obstructions that could greatly affect the image quality of the monitoring video, like laser glare by the tissue and body fluid, air bubbles and debris generated by tissue evaporation, and bleeding, just to name a few. In order to improve the physician's visual experience of a laser surgical procedure, the system performance parameter related to image quality needs to be well defined. However, since image quality is the integrated set of perceptions of the overall degree of excellence of an image, or in other words, image quality is the perceptually weighted combination of significant attributes (contrast, graininess …) of an image when considered in its marketplace or application, there is no standard definition on overall image or video quality especially for the no-reference case (without a standard chart as reference). In this study, Subjective Quality Factor (SQF) and acutance are used for no-reference image quality evaluation. Basic image quality parameters, like sharpness, color accuracy, size of obstruction and transmission of obstruction, are used as subparameter to define the rating scale for image quality evaluation or comparison. Sample image groups were evaluated by human observers according to the rating scale. Surveys of physician groups were also conducted with lab generated sample videos. The study shows that human subjective perception is a trustworthy way of image quality evaluation. More systematic investigation on the relationship between video quality and image quality of each frame will be conducted as a future study.

Modified-BRISQUE as no reference image quality assessment for structural MR images.

PubMed

Chow, Li Sze; Rajagopal, Heshalini

2017-11-01

An effective and practical Image Quality Assessment (IQA) model is needed to assess the image quality produced from any new hardware or software in MRI. A highly competitive No Reference - IQA (NR - IQA) model called Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) initially designed for natural images were modified to evaluate structural MR images. The BRISQUE model measures the image quality by using the locally normalized luminance coefficients, which were used to calculate the image features. The modified-BRISQUE model trained a new regression model using MR image features and Difference Mean Opinion Score (DMOS) from 775 MR images. Two types of benchmarks: objective and subjective assessments were used as performance evaluators for both original and modified-BRISQUE models. There was a high correlation between the modified-BRISQUE with both benchmarks, and they were higher than those for the original BRISQUE. There was a significant percentage improvement in their correlation values. The modified-BRISQUE was statistically better than the original BRISQUE. The modified-BRISQUE model can accurately measure the image quality of MR images. It is a practical NR-IQA model for MR images without using reference images. Copyright © 2017 Elsevier Inc. All rights reserved.

A comprehensive study on the relationship between the image quality and imaging dose in low-dose cone beam CT

NASA Astrophysics Data System (ADS)

Yan, Hao; Cervino, Laura; Jia, Xun; Jiang, Steve B.

2012-04-01

While compressed sensing (CS)-based algorithms have been developed for the low-dose cone beam CT (CBCT) reconstruction, a clear understanding of the relationship between the image quality and imaging dose at low-dose levels is needed. In this paper, we qualitatively investigate this subject in a comprehensive manner with extensive experimental and simulation studies. The basic idea is to plot both the image quality and imaging dose together as functions of the number of projections and mAs per projection over the whole clinically relevant range. On this basis, a clear understanding of the tradeoff between the image quality and imaging dose can be achieved and optimal low-dose CBCT scan protocols can be developed to maximize the dose reduction while minimizing the image quality loss for various imaging tasks in image-guided radiation therapy (IGRT). Main findings of this work include (1) under the CS-based reconstruction framework, image quality has little degradation over a large range of dose variation. Image quality degradation becomes evident when the imaging dose (approximated with the x-ray tube load) is decreased below 100 total mAs. An imaging dose lower than 40 total mAs leads to a dramatic image degradation, and thus should be used cautiously. Optimal low-dose CBCT scan protocols likely fall in the dose range of 40-100 total mAs, depending on the specific IGRT applications. (2) Among different scan protocols at a constant low-dose level, the super sparse-view reconstruction with the projection number less than 50 is the most challenging case, even with strong regularization. Better image quality can be acquired with low mAs protocols. (3) The optimal scan protocol is the combination of a medium number of projections and a medium level of mAs/view. This is more evident when the dose is around 72.8 total mAs or below and when the ROI is a low-contrast or high-resolution object. Based on our results, the optimal number of projections is around 90 to 120. (4

Kindergarten Classroom Quality, Behavioral Engagement, and Reading Achievement

ERIC Educational Resources Information Center

Ponitz, Claire Cameron; Rimm-Kaufman, Sara E.; Grimm, Kevin J.; Curby, Timothy W.

2009-01-01

This study examined the extent to which kindergarteners' classroom behavioral engagement mediated the relation between global classroom quality and children's reading achievement. A structural equation framework was used to analyze data collected in a primarily low-income rural sample (N = 171). Children's reading achievement was measured in the…

Quantitative image quality evaluation of MR images using perceptual difference models

PubMed Central

Miao, Jun; Huo, Donglai; Wilson, David L.

2008-01-01

The authors are using a perceptual difference model (Case-PDM) to quantitatively evaluate image quality of the thousands of test images which can be created when optimizing fast magnetic resonance (MR) imaging strategies and reconstruction techniques. In this validation study, they compared human evaluation of MR images from multiple organs and from multiple image reconstruction algorithms to Case-PDM and similar models. The authors found that Case-PDM compared very favorably to human observers in double-stimulus continuous-quality scale and functional measurement theory studies over a large range of image quality. The Case-PDM threshold for nonperceptible differences in a 2-alternative forced choice study varied with the type of image under study, but was ≈1.1 for diffuse image effects, providing a rule of thumb. Ordering the image quality evaluation models, we found in overall Case-PDM ≈ IDM (Sarnoff Corporation) ≈ SSIM [Wang et al. IEEE Trans. Image Process. 13, 600–612 (2004)] > mean squared error ≈ NR [Wang et al. (2004) (unpublished)] > DCTune (NASA) > IQM (MITRE Corporation). The authors conclude that Case-PDM is very useful in MR image evaluation but that one should probably restrict studies to similar images and similar processing, normally not a limitation in image reconstruction studies. PMID:18649487

Retinal image quality assessment based on image clarity and content

NASA Astrophysics Data System (ADS)

Abdel-Hamid, Lamiaa; El-Rafei, Ahmed; El-Ramly, Salwa; Michelson, Georg; Hornegger, Joachim

2016-09-01

Retinal image quality assessment (RIQA) is an essential step in automated screening systems to avoid misdiagnosis caused by processing poor quality retinal images. A no-reference transform-based RIQA algorithm is introduced that assesses images based on five clarity and content quality issues: sharpness, illumination, homogeneity, field definition, and content. Transform-based RIQA algorithms have the advantage of considering retinal structures while being computationally inexpensive. Wavelet-based features are proposed to evaluate the sharpness and overall illumination of the images. A retinal saturation channel is designed and used along with wavelet-based features for homogeneity assessment. The presented sharpness and illumination features are utilized to assure adequate field definition, whereas color information is used to exclude nonretinal images. Several publicly available datasets of varying quality grades are utilized to evaluate the feature sets resulting in area under the receiver operating characteristic curve above 0.99 for each of the individual feature sets. The overall quality is assessed by a classifier that uses the collective features as an input vector. The classification results show superior performance of the algorithm in comparison to other methods from literature. Moreover, the algorithm addresses efficiently and comprehensively various quality issues and is suitable for automatic screening systems.

Remote Sensing Image Quality Assessment Experiment with Post-Processing

NASA Astrophysics Data System (ADS)

Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.

2018-04-01

This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.

Subjective matters: from image quality to image psychology

NASA Astrophysics Data System (ADS)

Fedorovskaya, Elena A.; De Ridder, Huib

2013-03-01

From the advent of digital imaging through several decades of studies, the human vision research community systematically focused on perceived image quality and digital artifacts due to resolution, compression, gamma, dynamic range, capture and reproduction noise, blur, etc., to help overcome existing technological challenges and shortcomings. Technological advances made digital images and digital multimedia nearly flawless in quality, and ubiquitous and pervasive in usage, provide us with the exciting but at the same time demanding possibility to turn to the domain of human experience including higher psychological functions, such as cognition, emotion, awareness, social interaction, consciousness and Self. In this paper we will outline the evolution of human centered multidisciplinary studies related to imaging and propose steps and potential foci of future research.

Feature maps driven no-reference image quality prediction of authentically distorted images

NASA Astrophysics Data System (ADS)

Ghadiyaram, Deepti; Bovik, Alan C.

2015-03-01

Current blind image quality prediction models rely on benchmark databases comprised of singly and synthetically distorted images, thereby learning image features that are only adequate to predict human perceived visual quality on such inauthentic distortions. However, real world images often contain complex mixtures of multiple distortions. Rather than a) discounting the effect of these mixtures of distortions on an image's perceptual quality and considering only the dominant distortion or b) using features that are only proven to be efficient for singly distorted images, we deeply study the natural scene statistics of authentically distorted images, in different color spaces and transform domains. We propose a feature-maps-driven statistical approach which avoids any latent assumptions about the type of distortion(s) contained in an image, and focuses instead on modeling the remarkable consistencies in the scene statistics of real world images in the absence of distortions. We design a deep belief network that takes model-based statistical image features derived from a very large database of authentically distorted images as input and discovers good feature representations by generalizing over different distortion types, mixtures, and severities, which are later used to learn a regressor for quality prediction. We demonstrate the remarkable competence of our features for improving automatic perceptual quality prediction on a benchmark database and on the newly designed LIVE Authentic Image Quality Challenge Database and show that our approach of combining robust statistical features and the deep belief network dramatically outperforms the state-of-the-art.

Objective quality assessment for multiexposure multifocus image fusion.

PubMed

Hassen, Rania; Wang, Zhou; Salama, Magdy M A

2015-09-01

There has been a growing interest in image fusion technologies, but how to objectively evaluate the quality of fused images has not been fully understood. Here, we propose a method for objective quality assessment of multiexposure multifocus image fusion based on the evaluation of three key factors of fused image quality: 1) contrast preservation; 2) sharpness; and 3) structure preservation. Subjective experiments are conducted to create an image fusion database, based on which, performance evaluation shows that the proposed fusion quality index correlates well with subjective scores, and gives a significant improvement over the existing fusion quality measures.

No-reference image quality assessment for horizontal-path imaging scenarios

NASA Astrophysics Data System (ADS)

Rios, Carlos; Gladysz, Szymon

2013-05-01

There exist several image-enhancement algorithms and tasks associated with imaging through turbulence that depend on defining the quality of an image. Examples include: "lucky imaging", choosing the width of the inverse filter for image reconstruction, or stopping iterative deconvolution. We collected a number of image quality metrics found in the literature. Particularly interesting are the blind, "no-reference" metrics. We discuss ways of evaluating the usefulness of these metrics, even when a fully objective comparison is impossible because of the lack of a reference image. Metrics are tested on simulated and real data. Field data comes from experiments performed by the NATO SET 165 research group over a 7 km distance in Dayton, Ohio.

Guidance for Efficient Small Animal Imaging Quality Control.

PubMed

Osborne, Dustin R; Kuntner, Claudia; Berr, Stuart; Stout, David

2017-08-01

Routine quality control is a critical aspect of properly maintaining high-performance small animal imaging instrumentation. A robust quality control program helps produce more reliable data both for academic purposes and as proof of system performance for contract imaging work. For preclinical imaging laboratories, the combination of costs and available resources often limits their ability to produce efficient and effective quality control programs. This work presents a series of simplified quality control procedures that are accessible to a wide range of preclinical imaging laboratories. Our intent is to provide minimum guidelines for routine quality control that can assist preclinical imaging specialists in setting up an appropriate quality control program for their facility.

The effect of image sharpness on quantitative eye movement data and on image quality evaluation while viewing natural images

NASA Astrophysics Data System (ADS)

Vuori, Tero; Olkkonen, Maria

2006-01-01

The aim of the study is to test both customer image quality rating (subjective image quality) and physical measurement of user behavior (eye movements tracking) to find customer satisfaction differences in imaging technologies. Methodological aim is to find out whether eye movements could be quantitatively used in image quality preference studies. In general, we want to map objective or physically measurable image quality to subjective evaluations and eye movement data. We conducted a series of image quality tests, in which the test subjects evaluated image quality while we recorded their eye movements. Results show that eye movement parameters consistently change according to the instructions given to the user, and according to physical image quality, e.g. saccade duration increased with increasing blur. Results indicate that eye movement tracking could be used to differentiate image quality evaluation strategies that the users have. Results also show that eye movements would help mapping between technological and subjective image quality. Furthermore, these results give some empirical emphasis to top-down perception processes in image quality perception and evaluation by showing differences between perceptual processes in situations when cognitive task varies.

SU-F-I-47: Optimizing Protocols for Image Quality and Dose in Abdominal CT of Large Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, L; Yester, M

Purpose: Newer CT scanners are able to use scout views to adjust mA throughout the scan in order to achieve a given noise level. However, given constraints of radiologist preferences for kVp and rotation time, it may not be possible to achieve an acceptable noise level for large patients. A study was initiated to determine for which patients kVp and/or rotation time should be changed in order to achieve acceptable image quality. Methods: Patient scans were reviewed on two new Emergency Department scanners (Philips iCT) to identify patients over a large range of sizes. These iCTs were set with amore » limit of 500 mA to safeguard against a failure that might cause a CT scan to be (incorrectly) obtained at too-high mA. Scout views of these scans were assessed for both AP and LAT patient width and AP and LAT standard deviation in an ROI over the liver. Effective diameter and product of the scout standard deviations over the liver were both studied as possible metrics for identifying patients who would need kVp and/or rotation time changed. The mA used for the liver in the CT was compared to these metrics for those patients whose CT scans showed acceptable image quality. Results: Both effective diameter and product of the scout standard deviations over the liver result in similar predictions for which patients will require the kVp and/or rotation time to be changed to achieve an optimal combination of image quality and dose. Conclusion: Two mechanisms for CT technologists to determine based on scout characteristics what kVp, mA limit, and rotation time to use when DoseRight with our physicians’ preferred kVp and rotation time will not yield adequate image quality are described.« less

Comparison of image quality and radiation dose between split-filter dual-energy images and single-energy images in single-source abdominal CT.

PubMed

Euler, André; Obmann, Markus M; Szucs-Farkas, Zsolt; Mileto, Achille; Zaehringer, Caroline; Falkowski, Anna L; Winkel, David J; Marin, Daniele; Stieltjes, Bram; Krauss, Bernhard; Schindera, Sebastian T

2018-02-19

To compare image quality and radiation dose of abdominal split-filter dual-energy CT (SF-DECT) combined with monoenergetic imaging to single-energy CT (SECT) with automatic tube voltage selection (ATVS). Two-hundred single-source abdominal CT scans were performed as SECT with ATVS (n = 100) and SF-DECT (n = 100). SF-DECT scans were reconstructed and subdivided into composed images (SF-CI) and monoenergetic images at 55 keV (SF-MI). Objective and subjective image quality were compared among single-energy images (SEI), SF-CI and SF-MI. CNR and FOM were separately calculated for the liver (e.g. CNR liv ) and the portal vein (CNR pv ). Radiation dose was compared using size-specific dose estimate (SSDE). Results of the three groups were compared using non-parametric tests. Image noise of SF-CI was 18% lower compared to SEI and 48% lower compared to SF-MI (p < 0.001). Composed images yielded higher CNR liv over single-energy images (23.4 vs. 20.9; p < 0.001), whereas CNR pv was significantly lower (3.5 vs. 5.2; p < 0.001). Monoenergetic images overcame this inferiority in CNR pv and achieved similar results compared to single-energy images (5.1 vs. 5.2; p > 0.628). Subjective sharpness was equal between single-energy and monoenergetic images and diagnostic confidence was equal between single-energy and composed images. FOM liv was highest for SF-CI. FOM pv was equal for SEI and SF-MI (p = 0.78). SSDE was significant lower for SF-DECT compared to SECT (p < 0.022). The combined use of split-filter dual-energy CT images provides comparable objective and subjective image quality at lower radiation dose compared to single-energy CT with ATVS. • Split-filter dual-energy results in 18% lower noise compared to single-energy with ATVS. • Split-filter dual-energy results in 11% lower SSDE compared to single-energy with ATVS. • Spectral shaping of split-filter dual-energy leads to an increased dose-efficiency.

The impact of the condenser on cytogenetic image quality in digital microscope system.

PubMed

Ren, Liqiang; Li, Zheng; Li, Yuhua; Zheng, Bin; Li, Shibo; Chen, Xiaodong; Liu, Hong

2013-01-01

Optimizing operational parameters of the digital microscope system is an important technique to acquire high quality cytogenetic images and facilitate the process of karyotyping so that the efficiency and accuracy of diagnosis can be improved. This study investigated the impact of the condenser on cytogenetic image quality and system working performance using a prototype digital microscope image scanning system. Both theoretical analysis and experimental validations through objectively evaluating a resolution test chart and subjectively observing large numbers of specimen were conducted. The results show that the optimal image quality and large depth of field (DOF) are simultaneously obtained when the numerical aperture of condenser is set as 60%-70% of the corresponding objective. Under this condition, more analyzable chromosomes and diagnostic information are obtained. As a result, the system shows higher working stability and less restriction for the implementation of algorithms such as autofocusing especially when the system is designed to achieve high throughput continuous image scanning. Although the above quantitative results were obtained using a specific prototype system under the experimental conditions reported in this paper, the presented evaluation methodologies can provide valuable guidelines for optimizing operational parameters in cytogenetic imaging using the high throughput continuous scanning microscopes in clinical practice.

The Impact of the Condenser on Cytogenetic Image Quality in Digital Microscope System

PubMed Central

Ren, Liqiang; Li, Zheng; Li, Yuhua; Zheng, Bin; Li, Shibo; Chen, Xiaodong; Liu, Hong

2013-01-01

Background: Optimizing operational parameters of the digital microscope system is an important technique to acquire high quality cytogenetic images and facilitate the process of karyotyping so that the efficiency and accuracy of diagnosis can be improved. OBJECTIVE: This study investigated the impact of the condenser on cytogenetic image quality and system working performance using a prototype digital microscope image scanning system. Methods: Both theoretical analysis and experimental validations through objectively evaluating a resolution test chart and subjectively observing large numbers of specimen were conducted. Results: The results show that the optimal image quality and large depth of field (DOF) are simultaneously obtained when the numerical aperture of condenser is set as 60%–70% of the corresponding objective. Under this condition, more analyzable chromosomes and diagnostic information are obtained. As a result, the system shows higher working stability and less restriction for the implementation of algorithms such as autofocusing especially when the system is designed to achieve high throughput continuous image scanning. Conclusions: Although the above quantitative results were obtained using a specific prototype system under the experimental conditions reported in this paper, the presented evaluation methodologies can provide valuable guidelines for optimizing operational parameters in cytogenetic imaging using the high throughput continuous scanning microscopes in clinical practice. PMID:23676284

Objective quality assessment of tone-mapped images.

PubMed

Yeganeh, Hojatollah; Wang, Zhou

2013-02-01

Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. Different TMOs create different tone-mapped images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-mapped images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural images. Validations using independent subject-rated image databases show good correlations between subjective ranking score and the proposed tone-mapped image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples-parameter tuning for TMOs and adaptive fusion of multiple tone-mapped images.

Low-cost oblique illumination: an image quality assessment.

PubMed

Ruiz-Santaquiteria, Jesus; Espinosa-Aranda, Jose Luis; Deniz, Oscar; Sanchez, Carlos; Borrego-Ramos, Maria; Blanco, Saul; Cristobal, Gabriel; Bueno, Gloria

2018-01-01

We study the effectiveness of several low-cost oblique illumination filters to improve overall image quality, in comparison with standard bright field imaging. For this purpose, a dataset composed of 3360 diatom images belonging to 21 taxa was acquired. Subjective and objective image quality assessments were done. The subjective evaluation was performed by a group of diatom experts by psychophysical test where resolution, focus, and contrast were assessed. Moreover, some objective nonreference image quality metrics were applied to the same image dataset to complete the study, together with the calculation of several texture features to analyze the effect of these filters in terms of textural properties. Both image quality evaluation methods, subjective and objective, showed better results for images acquired using these illumination filters in comparison with the no filtered image. These promising results confirm that this kind of illumination filters can be a practical way to improve the image quality, thanks to the simple and low cost of the design and manufacturing process. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Quality metrics for sensor images

NASA Technical Reports Server (NTRS)

Ahumada, AL

1993-01-01

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery

A Dynamic Image Quality Evaluation of Videofluoroscopy Images: Considerations for Telepractice Applications.

PubMed

Burns, Clare L; Keir, Benjamin; Ward, Elizabeth C; Hill, Anne J; Farrell, Anna; Phillips, Nick; Porter, Linda

2015-08-01

High-quality fluoroscopy images are required for accurate interpretation of videofluoroscopic swallow studies (VFSS) by speech pathologists and radiologists. Consequently, integral to developing any system to conduct VFSS remotely via telepractice is ensuring that the quality of the VFSS images transferred via the telepractice system is optimized. This study evaluates the extent of change observed in image quality when videofluoroscopic images are transmitted from a digital fluoroscopy system to (a) current clinical equipment (KayPentax Digital Swallowing Workstation, and b) four different telepractice system configurations. The telepractice system configurations consisted of either a local C20 or C60 Cisco TelePresence System (codec unit) connected to the digital fluoroscopy system and linked to a second remote C20 or C60 Cisco TelePresence System via a network running at speeds of either 2, 4 or 6 megabits per second (Mbit/s). Image quality was tested using the NEMA XR 21 Phantom, and results demonstrated some loss in spatial resolution, low contrast detectability and temporal resolution for all transferred images when compared to the fluoroscopy source. When using higher capacity codec units and/or the highest bandwidths to support data transmission, image quality transmitted through the telepractice system was found to be comparable if not better than the current clinical system. This study confirms that telepractice systems can be designed to support fluoroscopy image transfer and highlights important considerations when developing telepractice systems for VFSS analysis to ensure high-quality radiological image reproduction.

Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

NASA Astrophysics Data System (ADS)

Dong, Jian; Kudo, Hiroyuki

2017-03-01

Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

Comparing hardcopy and softcopy results in the study of the impact of workflow on perceived reproduction quality of fine art images

NASA Astrophysics Data System (ADS)

Farnand, Susan; Jiang, Jun; Frey, Franziska

2011-01-01

A project, supported by the Andrew W. Mellon Foundation, is currently underway to evaluate current practices in fine art image reproduction, determine the image quality generally achievable, and establish a suggested framework for art image interchange. To determine the image quality currently being achieved, experimentation has been conducted in which a set of objective targets and pieces of artwork in various media were imaged by participating museums and other cultural heritage institutions. Prints and images for display made from the delivered image files at the Rochester Institute of Technology were used as stimuli in psychometric testing in which observers were asked to evaluate the prints as reproductions of the original artwork and as stand alone images. The results indicated that there were limited differences between assessments made using displayed images relative to printed reproductions. Further, the differences between rankings made with and without the original artwork present were much smaller than expected.

Perceptual full-reference quality assessment of stereoscopic images by considering binocular visual characteristics.

PubMed

Shao, Feng; Lin, Weisi; Gu, Shanbo; Jiang, Gangyi; Srikanthan, Thambipillai

2013-05-01

Perceptual quality assessment is a challenging issue in 3D signal processing research. It is important to study 3D signal directly instead of studying simple extension of the 2D metrics directly to the 3D case as in some previous studies. In this paper, we propose a new perceptual full-reference quality assessment metric of stereoscopic images by considering the binocular visual characteristics. The major technical contribution of this paper is that the binocular perception and combination properties are considered in quality assessment. To be more specific, we first perform left-right consistency checks and compare matching error between the corresponding pixels in binocular disparity calculation, and classify the stereoscopic images into non-corresponding, binocular fusion, and binocular suppression regions. Also, local phase and local amplitude maps are extracted from the original and distorted stereoscopic images as features in quality assessment. Then, each region is evaluated independently by considering its binocular perception property, and all evaluation results are integrated into an overall score. Besides, a binocular just noticeable difference model is used to reflect the visual sensitivity for the binocular fusion and suppression regions. Experimental results show that compared with the relevant existing metrics, the proposed metric can achieve higher consistency with subjective assessment of stereoscopic images.

Low-Achieving Readers, High Expectations: Image Theatre Encourages Critical Literacy

ERIC Educational Resources Information Center

Rozansky, Carol Lloyd; Aagesen, Colleen

2010-01-01

Students in an eighth-grade, urban, low-achieving reading class were introduced to critical literacy through engagement in Image Theatre. Developed by liberatory dramatist Augusto Boal, Image Theatre gives participants the opportunity to examine texts in the triple role of interpreter, artist, and sculptor (i.e., image creator). The researchers…

Using collective expert judgements to evaluate quality measures of mass spectrometry images.

PubMed

Palmer, Andrew; Ovchinnikova, Ekaterina; Thuné, Mikael; Lavigne, Régis; Guével, Blandine; Dyatlov, Andrey; Vitek, Olga; Pineau, Charles; Borén, Mats; Alexandrov, Theodore

2015-06-15

Imaging mass spectrometry (IMS) is a maturating technique of molecular imaging. Confidence in the reproducible quality of IMS data is essential for its integration into routine use. However, the predominant method for assessing quality is visual examination, a time consuming, unstandardized and non-scalable approach. So far, the problem of assessing the quality has only been marginally addressed and existing measures do not account for the spatial information of IMS data. Importantly, no approach exists for unbiased evaluation of potential quality measures. We propose a novel approach for evaluating potential measures by creating a gold-standard set using collective expert judgements upon which we evaluated image-based measures. To produce a gold standard, we engaged 80 IMS experts, each to rate the relative quality between 52 pairs of ion images from MALDI-TOF IMS datasets of rat brain coronal sections. Experts' optional feedback on their expertise, the task and the survey showed that (i) they had diverse backgrounds and sufficient expertise, (ii) the task was properly understood, and (iii) the survey was comprehensible. A moderate inter-rater agreement was achieved with Krippendorff's alpha of 0.5. A gold-standard set of 634 pairs of images with accompanying ratings was constructed and showed a high agreement of 0.85. Eight families of potential measures with a range of parameters and statistical descriptors, giving 143 in total, were evaluated. Both signal-to-noise and spatial chaos-based measures performed highly with a correlation of 0.7 to 0.9 with the gold standard ratings. Moreover, we showed that a composite measure with the linear coefficients (trained on the gold standard with regularized least squares optimization and lasso) showed a strong linear correlation of 0.94 and an accuracy of 0.98 in predicting which image in a pair was of higher quality. The anonymized data collected from the survey and the Matlab source code for data processing can be found

Using collective expert judgements to evaluate quality measures of mass spectrometry images

PubMed Central

Palmer, Andrew; Ovchinnikova, Ekaterina; Thuné, Mikael; Lavigne, Régis; Guével, Blandine; Dyatlov, Andrey; Vitek, Olga; Pineau, Charles; Borén, Mats; Alexandrov, Theodore

2015-01-01

Motivation: Imaging mass spectrometry (IMS) is a maturating technique of molecular imaging. Confidence in the reproducible quality of IMS data is essential for its integration into routine use. However, the predominant method for assessing quality is visual examination, a time consuming, unstandardized and non-scalable approach. So far, the problem of assessing the quality has only been marginally addressed and existing measures do not account for the spatial information of IMS data. Importantly, no approach exists for unbiased evaluation of potential quality measures. Results: We propose a novel approach for evaluating potential measures by creating a gold-standard set using collective expert judgements upon which we evaluated image-based measures. To produce a gold standard, we engaged 80 IMS experts, each to rate the relative quality between 52 pairs of ion images from MALDI-TOF IMS datasets of rat brain coronal sections. Experts’ optional feedback on their expertise, the task and the survey showed that (i) they had diverse backgrounds and sufficient expertise, (ii) the task was properly understood, and (iii) the survey was comprehensible. A moderate inter-rater agreement was achieved with Krippendorff’s alpha of 0.5. A gold-standard set of 634 pairs of images with accompanying ratings was constructed and showed a high agreement of 0.85. Eight families of potential measures with a range of parameters and statistical descriptors, giving 143 in total, were evaluated. Both signal-to-noise and spatial chaos-based measures performed highly with a correlation of 0.7 to 0.9 with the gold standard ratings. Moreover, we showed that a composite measure with the linear coefficients (trained on the gold standard with regularized least squares optimization and lasso) showed a strong linear correlation of 0.94 and an accuracy of 0.98 in predicting which image in a pair was of higher quality. Availability and implementation: The anonymized data collected from the survey

Standardizing Quality Assessment of Fused Remotely Sensed Images

NASA Astrophysics Data System (ADS)

Pohl, C.; Moellmann, J.; Fries, K.

2017-09-01

The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.

Automating PACS quality control with the Vanderbilt image processing enterprise resource

NASA Astrophysics Data System (ADS)

Esparza, Michael L.; Welch, E. Brian; Landman, Bennett A.

2012-02-01

Precise image acquisition is an integral part of modern patient care and medical imaging research. Periodic quality control using standardized protocols and phantoms ensures that scanners are operating according to specifications, yet such procedures do not ensure that individual datasets are free from corruption; for example due to patient motion, transient interference, or physiological variability. If unacceptable artifacts are noticed during scanning, a technologist can repeat a procedure. Yet, substantial delays may be incurred if a problematic scan is not noticed until a radiologist reads the scans or an automated algorithm fails. Given scores of slices in typical three-dimensional scans and widevariety of potential use cases, a technologist cannot practically be expected inspect all images. In large-scale research, automated pipeline systems have had great success in achieving high throughput. However, clinical and institutional workflows are largely based on DICOM and PACS technologies; these systems are not readily compatible with research systems due to security and privacy restrictions. Hence, quantitative quality control has been relegated to individual investigators and too often neglected. Herein, we propose a scalable system, the Vanderbilt Image Processing Enterprise Resource (VIPER) to integrate modular quality control and image analysis routines with a standard PACS configuration. This server unifies image processing routines across an institutional level and provides a simple interface so that investigators can collaborate to deploy new analysis technologies. VIPER integrates with high performance computing environments has successfully analyzed all standard scans from our institutional research center over the course of the last 18 months.

Image quality evaluation of full reference algorithm

NASA Astrophysics Data System (ADS)

He, Nannan; Xie, Kai; Li, Tong; Ye, Yushan

2018-03-01

Image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity Image Metric(SSIM) and feature similarity(FSIM) of objective evaluation methods. The different evaluation methods are tested by Matlab, and the advantages and disadvantages of these methods are obtained by analyzing and comparing them.MSE and PSNR are simple, but they are not considered to introduce HVS characteristics into image quality evaluation. The evaluation result is not ideal. SSIM has a good correlation and simple calculation ,because it is considered to the human visual effect into image quality evaluation,However the SSIM method is based on a hypothesis,The evaluation result is limited. The FSIM method can be used for test of gray image and color image test, and the result is better. Experimental results show that the new image quality evaluation algorithm based on FSIM is more accurate.

A Lifespan Perspective on Adults' Achievement and Life Quality.

ERIC Educational Resources Information Center

Steel, Lauri; Wise, Lauress L.

This paper explores how life course organization influences overall life quality and achievement, with emphasis on achievement differences between men and women. Life course organization refers to the level, timing, sequencing, and continuity of educational, occupational, marital, childbearing, and other commitments made by an individual over a…

High-quality compressive ghost imaging

NASA Astrophysics Data System (ADS)

Huang, Heyan; Zhou, Cheng; Tian, Tian; Liu, Dongqi; Song, Lijun

2018-04-01

We propose a high-quality compressive ghost imaging method based on projected Landweber regularization and guided filter, which effectively reduce the undersampling noise and improve the resolution. In our scheme, the original object is reconstructed by decomposing of regularization and denoising steps instead of solving a minimization problem in compressive reconstruction process. The simulation and experimental results show that our method can obtain high ghost imaging quality in terms of PSNR and visual observation.

Examples of subjective image quality enhancement in multimedia

NASA Astrophysics Data System (ADS)

Klíma, Miloš; Pazderák, Jiří; Fliegel, Karel

2007-09-01

The subjective image quality is an important issue in all multimedia imaging systems with a significant impact onto QoS (Quality of Service). For long time the image fidelity criterion was widely applied in technical systems esp. in both television and image source compression fields but the optimization of subjective perception quality and fidelity approach (such as the minimum of MSE) are very different. The paper presents an experimental testing of three different digital techniques for the subjective image quality enhancement - color saturation, edge enhancement, denoising operators and noise addition - well known from both the digital photography and video. The evaluation has been done for extensive operator parameterization and the results are summarized and discussed. It has been demonstrated that there are relevant types of image corrections improving to some extent the subjective perception of the image. The above mentioned techniques have been tested for five image tests with significantly different image characteristics (fine details, large saturated color areas, high color contrast, easy-to-remember colors etc.). The experimental results show the way to optimized use of image enhancing operators. Finally the concept of impressiveness as a new possible expression of subjective quality improvement is presented and discussed.

Performance evaluation of no-reference image quality metrics for face biometric images

NASA Astrophysics Data System (ADS)

Liu, Xinwei; Pedersen, Marius; Charrier, Christophe; Bours, Patrick

2018-03-01

The accuracy of face recognition systems is significantly affected by the quality of face sample images. The recent established standardization proposed several important aspects for the assessment of face sample quality. There are many existing no-reference image quality metrics (IQMs) that are able to assess natural image quality by taking into account similar image-based quality attributes as introduced in the standardization. However, whether such metrics can assess face sample quality is rarely considered. We evaluate the performance of 13 selected no-reference IQMs on face biometrics. The experimental results show that several of them can assess face sample quality according to the system performance. We also analyze the strengths and weaknesses of different IQMs as well as why some of them failed to assess face sample quality. Retraining an original IQM by using face database can improve the performance of such a metric. In addition, the contribution of this paper can be used for the evaluation of IQMs on other biometric modalities; furthermore, it can be used for the development of multimodality biometric IQMs.

A qualitative and quantitative analysis of radiation dose and image quality of computed tomography images using adaptive statistical iterative reconstruction.

PubMed

Hussain, Fahad Ahmed; Mail, Noor; Shamy, Abdulrahman M; Suliman, Alghamdi; Saoudi, Abdelhamid

2016-05-08

Image quality is a key issue in radiology, particularly in a clinical setting where it is important to achieve accurate diagnoses while minimizing radiation dose. Some computed tomography (CT) manufacturers have introduced algorithms that claim significant dose reduction. In this study, we assessed CT image quality produced by two reconstruction algorithms provided with GE Healthcare's Discovery 690 Elite positron emission tomography (PET) CT scanner. Image quality was measured for images obtained at various doses with both conventional filtered back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR) algorithms. A stan-dard CT dose index (CTDI) phantom and a pencil ionization chamber were used to measure the CT dose at 120 kVp and an exposure of 260 mAs. Image quality was assessed using two phantoms. CT images of both phantoms were acquired at tube voltage (kV) of 120 with exposures ranging from 25 mAs to 400 mAs. Images were reconstructed using FBP and ASIR ranging from 10% to 100%, then analyzed for noise, low-contrast detectability, contrast-to-noise ratio (CNR), and modulation transfer function (MTF). Noise was 4.6 HU in water phantom images acquired at 260 mAs/FBP 120 kV and 130 mAs/50% ASIR 120 kV. The large objects (fre-quency < 7 lp/cm) retained fairly acceptable image quality at 130 mAs/50% ASIR, compared to 260 mAs/FBP. The application of ASIR for small objects (frequency >7 lp/cm) showed poor visibility compared to FBP at 260 mAs and even worse for images acquired at less than 130 mAs. ASIR blending more than 50% at low dose tends to reduce contrast of small objects (frequency >7 lp/cm). We concluded that dose reduction and ASIR should be applied with close attention if the objects to be detected or diagnosed are small (frequency > 7 lp/cm). Further investigations are required to correlate the small objects (frequency > 7 lp/cm) to patient anatomy and clinical diagnosis.

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

PubMed

Wang, Shaoze; Jin, Kai; Lu, Haitong; Cheng, Chuming; Ye, Juan; Qian, Dahong

2016-04-01

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.

Design of a practical model-observer-based image quality assessment method for x-ray computed tomography imaging systems

PubMed Central

Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.

2016-01-01

Abstract. The use of a channelization mechanism on model observers not only makes mimicking human visual behavior possible, but also reduces the amount of image data needed to estimate the model observer parameters. The channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) have recently been used to assess CT image quality for detection tasks and combined detection/estimation tasks, respectively. Although the use of channels substantially reduces the amount of data required to compute image quality, the number of scans required for CT imaging is still not practical for routine use. It is our desire to further reduce the number of scans required to make CHO or CSLO an image quality tool for routine and frequent system validations and evaluations. This work explores different data-reduction schemes and designs an approach that requires only a few CT scans. Three different kinds of approaches are included in this study: a conventional CHO/CSLO technique with a large sample size, a conventional CHO/CSLO technique with fewer samples, and an approach that we will show requires fewer samples to mimic conventional performance with a large sample size. The mean value and standard deviation of areas under ROC/EROC curve were estimated using the well-validated shuffle approach. The results indicate that an 80% data reduction can be achieved without loss of accuracy. This substantial data reduction is a step toward a practical tool for routine-task-based QA/QC CT system assessment. PMID:27493982

Naturalness and interestingness of test images for visual quality evaluation

NASA Astrophysics Data System (ADS)

Halonen, Raisa; Westman, Stina; Oittinen, Pirkko

2011-01-01

Balanced and representative test images are needed to study perceived visual quality in various application domains. This study investigates naturalness and interestingness as image quality attributes in the context of test images. Taking a top-down approach we aim to find the dimensions which constitute naturalness and interestingness in test images and the relationship between these high-level quality attributes. We compare existing collections of test images (e.g. Sony sRGB images, ISO 12640 images, Kodak images, Nokia images and test images developed within our group) in an experiment combining quality sorting and structured interviews. Based on the data gathered we analyze the viewer-supplied criteria for naturalness and interestingness across image types, quality levels and judges. This study advances our understanding of subjective image quality criteria and enables the validation of current test images, furthering their development.

Evaluation of automatic image quality assessment in chest CT - A human cadaver study.

PubMed

Franck, Caro; De Crop, An; De Roo, Bieke; Smeets, Peter; Vergauwen, Merel; Dewaele, Tom; Van Borsel, Mathias; Achten, Eric; Van Hoof, Tom; Bacher, Klaus

2017-04-01

The evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers. Chest CT's of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized. Good correlations were found between IQs and the measured physical-technical image quality: noise (ρ=-1.00), contrast-to-noise (ρ=1.00) and contrast-detail (ρ=0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively. The automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Improving high resolution retinal image quality using speckle illumination HiLo imaging

PubMed Central

Zhou, Xiaolin; Bedggood, Phillip; Metha, Andrew

2014-01-01

Retinal image quality from flood illumination adaptive optics (AO) ophthalmoscopes is adversely affected by out-of-focus light scatter due to the lack of confocality. This effect is more pronounced in small eyes, such as that of rodents, because the requisite high optical power confers a large dioptric thickness to the retina. A recently-developed structured illumination microscopy (SIM) technique called HiLo imaging has been shown to reduce the effect of out-of-focus light scatter in flood illumination microscopes and produce pseudo-confocal images with significantly improved image quality. In this work, we adopted the HiLo technique to a flood AO ophthalmoscope and performed AO imaging in both (physical) model and live rat eyes. The improvement in image quality from HiLo imaging is shown both qualitatively and quantitatively by using spatial spectral analysis. PMID:25136486

Improving high resolution retinal image quality using speckle illumination HiLo imaging.

PubMed

Zhou, Xiaolin; Bedggood, Phillip; Metha, Andrew

2014-08-01

Retinal image quality from flood illumination adaptive optics (AO) ophthalmoscopes is adversely affected by out-of-focus light scatter due to the lack of confocality. This effect is more pronounced in small eyes, such as that of rodents, because the requisite high optical power confers a large dioptric thickness to the retina. A recently-developed structured illumination microscopy (SIM) technique called HiLo imaging has been shown to reduce the effect of out-of-focus light scatter in flood illumination microscopes and produce pseudo-confocal images with significantly improved image quality. In this work, we adopted the HiLo technique to a flood AO ophthalmoscope and performed AO imaging in both (physical) model and live rat eyes. The improvement in image quality from HiLo imaging is shown both qualitatively and quantitatively by using spatial spectral analysis.

Image Quality in High-resolution and High-cadence Solar Imaging

NASA Astrophysics Data System (ADS)

Denker, C.; Dineva, E.; Balthasar, H.; Verma, M.; Kuckein, C.; Diercke, A.; González Manrique, S. J.

2018-03-01

Broad-band imaging and even imaging with a moderate bandpass (about 1 nm) provides a photon-rich environment, where frame selection (lucky imaging) becomes a helpful tool in image restoration, allowing us to perform a cost-benefit analysis on how to design observing sequences for imaging with high spatial resolution in combination with real-time correction provided by an adaptive optics (AO) system. This study presents high-cadence (160 Hz) G-band and blue continuum image sequences obtained with the High-resolution Fast Imager (HiFI) at the 1.5-meter GREGOR solar telescope, where the speckle-masking technique is used to restore images with nearly diffraction-limited resolution. The HiFI employs two synchronized large-format and high-cadence sCMOS detectors. The median filter gradient similarity (MFGS) image-quality metric is applied, among others, to AO-corrected image sequences of a pore and a small sunspot observed on 2017 June 4 and 5. A small region of interest, which was selected for fast-imaging performance, covered these contrast-rich features and their neighborhood, which were part of Active Region NOAA 12661. Modifications of the MFGS algorithm uncover the field- and structure-dependency of this image-quality metric. However, MFGS still remains a good choice for determining image quality without a priori knowledge, which is an important characteristic when classifying the huge number of high-resolution images contained in data archives. In addition, this investigation demonstrates that a fast cadence and millisecond exposure times are still insufficient to reach the coherence time of daytime seeing. Nonetheless, the analysis shows that data acquisition rates exceeding 50 Hz are required to capture a substantial fraction of the best seeing moments, significantly boosting the performance of post-facto image restoration.

Implant image quality in dental radiographs recorded using a customized imaging guide or a standard film holder.

PubMed

Schropp, Lars; Stavropoulos, Andreas; Spin-Neto, Rubens; Wenzel, Ann

2012-01-01

To compare a customized imaging guide and a standard film holder for obtaining optimally projected intraoral radiographs of dental implants. Intraoral radiographs of four screw-type implants with different inclination placed in an upper or lower dental phantom model were recorded by 32 groups of examiners after a short instruction in the use of the RB-RB/LB-LB mnemonic rule. Half of the examiners recorded the images using a standard film holder and the other half used a customized imaging guide. Each radiograph was assessed under blinded conditions with regard to rendering of the implant threads and was assigned to one of four quality categories: (1) perfect, (2) not perfect, but clinically acceptable, (3) not acceptable, and (4) hopeless. For the upper jaw, the same number of exposures per implant were made to achieve an acceptable image (P=0.86) by the standard film holder method (median=2) and the imaging guide method (median=2). For the lower jaw, medians for the imaging guide method and the film holder method were 1 and 2, respectively (P=0.004). For the imaging guide method, the first exposure was rated as perfect/acceptable in 62% of the cases and for the film holder method in 41% of the cases (P=0.013). After ≤ 2 exposures, 78% (imaging guide method) and 69% (film holder method) of the implant images were perfect/acceptable (P=0.23). The implant inclination did not have a major influence on the outcomes. Perfect or acceptable images were achieved after two exposures with the same frequency either using a customized imaging guide method or a standard film holder method. However, the use of a customized imaging guide method was overall significantly superior to a standard film holder method in terms of obtaining perfect or acceptable images with only one exposure. © 2011 John Wiley & Sons A/S.

On pictures and stuff: image quality and material appearance

NASA Astrophysics Data System (ADS)

Ferwerda, James A.

2014-02-01

Realistic images are a puzzle because they serve as visual representations of objects while also being objects themselves. When we look at an image we are able to perceive both the properties of the image and the properties of the objects represented by the image. Research on image quality has typically focused improving image properties (resolution, dynamic range, frame rate, etc.) while ignoring the issue of whether images are serving their role as visual representations. In this paper we describe a series of experiments that investigate how well images of different quality convey information about the properties of the objects they represent. In the experiments we focus on the effects that two image properties (contrast and sharpness) have on the ability of images to represent the gloss of depicted objects. We found that different experimental methods produced differing results. Specifically, when the stimulus images were presented using simultaneous pair comparison, observers were influenced by the surface properties of the images and conflated changes in image contrast and sharpness with changes in object gloss. On the other hand, when the stimulus images were presented sequentially, observers were able to disregard the image plane properties and more accurately match the gloss of the objects represented by the different quality images. These findings suggest that in understanding image quality it is useful to distinguish between quality of the imaging medium and the quality of the visual information represented by that medium.

Achieving Kaiser Permanente Quality

PubMed Central

McHugh, Matthew D.; Aiken, Linda H.; Eckenhoff, Myra E.; Burns, Lawton R.

2015-01-01

Background The Kaiser Permanente model of integrated health delivery is highly regarded for high quality and efficient health care. Efforts to reproduce Kaiser’s success have mostly failed. One factor that has received little attention and that could explain Kaiser’s advantage is its commitment to and investment in nursing as a key component of organizational culture and patient-centered care. Purpose The aim of this study was to investigate the role of Kaiser’s nursing organization in promoting quality of care. Methodology This was a cross-sectional analysis of linked secondary data from multiple sources, including a detailed survey of nurses, for 564 adult, general acute care hospitals from California, Florida, Pennsylvania, and New Jersey in 2006–2007. We used logistic regression models to examine whether patient (mortality and failure-to-rescue) and nurse (burnout, job satisfaction, and intent-to-leave) outcomes in Kaiser hospitals were better than in non-Kaiser hospitals. We then assessed whether differences in nursing explained outcomes differences between Kaiser and other hospitals. Finally, we examined whether Kaiser hospitals compared favorably with hospitals known for having excellent nurse work environments — Magnet hospitals. Findings Patient and nurse outcomes in Kaiser hospitals were significantly better compared with non-Magnet hospitals. Kaiser hospitals had significantly better nurse work environments, staffing levels, and more nurses with bachelor’s degrees. Differences in nursing explained a significant proportion of the Kaiser outcomes advantage. Kaiser hospital outcomes were comparable to Magnet hospitals, where better outcomes have been largely explained by differences in nursing. Implications An important element in Kaiser’s success is its investment in professional nursing, which may not be evident to systems seeking to achieve Kaiser’s advantage. Our results suggest that a possible strategy for achieving outcomes like Kaiser

Exploring High-Achieving Students' Images of Mathematicians

ERIC Educational Resources Information Center

Aguilar, Mario Sánchez; Rosas, Alejandro; Zavaleta, Juan Gabriel Molina; Romo-Vázquez, Avenilde

2016-01-01

The aim of this study is to describe the images that a group of high-achieving Mexican students hold of mathematicians. For this investigation, we used a research method based on the Draw-A-Scientist Test (DAST) with a sample of 63 Mexican high school students. The group of students' pictorial and written descriptions of mathematicians assisted us…

Reduced reference image quality assessment via sub-image similarity based redundancy measurement

NASA Astrophysics Data System (ADS)

Mou, Xuanqin; Xue, Wufeng; Zhang, Lei

2012-03-01

The reduced reference (RR) image quality assessment (IQA) has been attracting much attention from researchers for its loyalty to human perception and flexibility in practice. A promising RR metric should be able to predict the perceptual quality of an image accurately while using as few features as possible. In this paper, a novel RR metric is presented, whose novelty lies in two aspects. Firstly, it measures the image redundancy by calculating the so-called Sub-image Similarity (SIS), and the image quality is measured by comparing the SIS between the reference image and the test image. Secondly, the SIS is computed by the ratios of NSE (Non-shift Edge) between pairs of sub-images. Experiments on two IQA databases (i.e. LIVE and CSIQ databases) show that by using only 6 features, the proposed metric can work very well with high correlations between the subjective and objective scores. In particular, it works consistently well across all the distortion types.

Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images.

PubMed

Favazza, Christopher P; Ferrero, Andrea; Yu, Lifeng; Leng, Shuai; McMillan, Kyle L; McCollough, Cynthia H

2017-07-01

The use of iterative reconstruction (IR) algorithms in CT generally decreases image noise and enables dose reduction. However, the amount of dose reduction possible using IR without sacrificing diagnostic performance is difficult to assess with conventional image quality metrics. Through this investigation, achievable dose reduction using a commercially available IR algorithm without loss of low contrast spatial resolution was determined with a channelized Hotelling observer (CHO) model and used to optimize a clinical abdomen/pelvis exam protocol. A phantom containing 21 low contrast disks-three different contrast levels and seven different diameters-was imaged at different dose levels. Images were created with filtered backprojection (FBP) and IR. The CHO was tasked with detecting the low contrast disks. CHO performance indicated dose could be reduced by 22% to 25% without compromising low contrast detectability (as compared to full-dose FBP images) whereas 50% or more dose reduction significantly reduced detection performance. Importantly, default settings for the scanner and protocol investigated reduced dose by upward of 75%. Subsequently, CHO-based protocol changes to the default protocol yielded images of higher quality and doses more consistent with values from a larger, dose-optimized scanner fleet. CHO assessment provided objective data to successfully optimize a clinical CT acquisition protocol.

Noise Estimation and Quality Assessment of Gaussian Noise Corrupted Images

NASA Astrophysics Data System (ADS)

Kamble, V. M.; Bhurchandi, K.

2018-03-01

Evaluating the exact quantity of noise present in an image and quality of an image in the absence of reference image is a challenging task. We propose a near perfect noise estimation method and a no reference image quality assessment method for images corrupted by Gaussian noise. The proposed methods obtain initial estimate of noise standard deviation present in an image using the median of wavelet transform coefficients and then obtains a near to exact estimate using curve fitting. The proposed noise estimation method provides the estimate of noise within average error of +/-4%. For quality assessment, this noise estimate is mapped to fit the Differential Mean Opinion Score (DMOS) using a nonlinear function. The proposed methods require minimum training and yields the noise estimate and image quality score. Images from Laboratory for image and Video Processing (LIVE) database and Computational Perception and Image Quality (CSIQ) database are used for validation of the proposed quality assessment method. Experimental results show that the performance of proposed quality assessment method is at par with the existing no reference image quality assessment metric for Gaussian noise corrupted images.

Image quality metrics for volumetric laser displays

NASA Astrophysics Data System (ADS)

Williams, Rodney D.; Donohoo, Daniel

1991-08-01

This paper addresses the extensions to the image quality metrics and related human factors research that are needed to establish the baseline standards for emerging volume display technologies. The existing and recently developed technologies for multiplanar volume displays are reviewed with an emphasis on basic human visual issues. Human factors image quality metrics and guidelines are needed to firmly establish this technology in the marketplace. The human visual requirements and the display design tradeoffs for these prototype laser-based volume displays are addressed and several critical image quality issues identified for further research. The American National Standard for Human Factors Engineering of Visual Display Terminal Workstations (ANSIHFS-100) and other international standards (ISO, DIN) can serve as a starting point, but this research base must be extended to provide new image quality metrics for this new technology for volume displays.

Does High School Facility Quality Affect Student Achievement? A Two-Level Hierarchical Linear Model

ERIC Educational Resources Information Center

Bowers, Alex J.; Urick, Angela

2011-01-01

The purpose of this study is to isolate the independent effects of high school facility quality on student achievement using a large, nationally representative U.S. database of student achievement and school facility quality. Prior research on linking school facility quality to student achievement has been mixed. Studies that relate overall…

Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

NASA Astrophysics Data System (ADS)

Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

2018-04-01

A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

Cartographic quality of ERTS-1 images

NASA Technical Reports Server (NTRS)

Welch, R. I.

1973-01-01

Analyses of simulated and operational ERTS images have provided initial estimates of resolution, ground resolution, detectability thresholds and other measures of image quality of interest to earth scientists and cartographers. Based on these values, including an approximate ground resolution of 250 meters for both RBV and MSS systems, the ERTS-1 images appear suited to the production and/or revision of planimetric and photo maps of 1:500,000 scale and smaller for which map accuracy standards are compatible with the imaged detail. Thematic mapping, although less constrained by map accuracy standards, will be influenced by measurement thresholds and errors which have yet to be accurately determined for ERTS images. This study also indicates the desirability of establishing a quantitative relationship between image quality values and map products which will permit both engineers and cartographers/earth scientists to contribute to the design requirements of future satellite imaging systems.

Development of Prior Image-based, High-Quality, Low-Dose Kilovoltage Cone Beam CT for Use in Adaptive Radiotherapy of Prostate Cancer

DTIC Science & Technology

2012-05-01

employs kilovoltage (KV) cone- beam CT (CBCT) for guiding treatment. High quality CBCT images are important in achieving improved treatment effect...necessary for achieving successful adaptive RT. Kilovoltage cone-beam CT (CBCT) has shown its capability of yielding such images to guide the prostate cancer...study of low-dose intra-operative cone-beam CT for image- guided surgery,” Proc. SPIE, 7961, 79615P, 2011 10. X. Han, E. Pearson, J. Bian, S. Cho, E. Y

Influence of reconstruction algorithms on image quality in SPECT myocardial perfusion imaging.

PubMed

Davidsson, Anette; Olsson, Eva; Engvall, Jan; Gustafsson, Agnetha

2017-11-01

We investigated if image- and diagnostic quality in SPECT MPI could be maintained despite a reduced acquisition time adding Depth Dependent Resolution Recovery (DDRR) for image reconstruction. Images were compared with filtered back projection (FBP) and iterative reconstruction using Ordered Subsets Expectation Maximization with (IRAC) and without (IRNC) attenuation correction (AC). Stress- and rest imaging for 15 min was performed on 21 subjects with a dual head gamma camera (Infinia Hawkeye; GE Healthcare), ECG-gating with 8 frames/cardiac cycle and a low-dose CT-scan. A 9 min acquisition was generated using five instead of eight gated frames and was reconstructed with DDRR, with (IRACRR) and without AC (IRNCRR) as well as with FBP. Three experienced nuclear medicine specialists visually assessed anonymized images according to eight criteria on a four point scale, three related to image quality and five to diagnostic confidence. Statistical analysis was performed using Visual Grading Regression (VGR). Observer confidence in statements on image quality was highest for the images that were reconstructed using DDRR (P<0·01 compared to FBP). Iterative reconstruction without DDRR was not superior to FBP. Interobserver variability was significant for statements on image quality (P<0·05) but lower in the diagnostic statements on ischemia and scar. The confidence in assessing ischemia and scar was not different between the reconstruction techniques (P = n.s.). SPECT MPI collected in 9 min, reconstructed with DDRR and AC, produced better image quality than the standard procedure. The observers expressed the highest diagnostic confidence in the DDRR reconstruction. © 2016 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Achieving quality assurance through clinical audit.

PubMed

Patel, Seraphim

2010-06-01

Audit is a crucial component of improvements to the quality of patient care. Clinical audits are undertaken to help ensure that patients can be given safe, reliable and dignified care, and to encourage them to self-direct their recovery. Such audits are undertaken also to help reduce lengths of patient stay in hospital, readmission rates and delays in discharge. This article describes the stages of clinical audit and the support required to achieve organisational core values.

The effect of image quality and forensic expertise in facial image comparisons.

PubMed

Norell, Kristin; Läthén, Klas Brorsson; Bergström, Peter; Rice, Allyson; Natu, Vaidehi; O'Toole, Alice

2015-03-01

Images of perpetrators in surveillance video footage are often used as evidence in court. In this study, identification accuracy was compared for forensic experts and untrained persons in facial image comparisons as well as the impact of image quality. Participants viewed thirty image pairs and were asked to rate the level of support garnered from their observations for concluding whether or not the two images showed the same person. Forensic experts reached their conclusions with significantly fewer errors than did untrained participants. They were also better than novices at determining when two high-quality images depicted the same person. Notably, lower image quality led to more careful conclusions by experts, but not for untrained participants. In summary, the untrained participants had more false negatives and false positives than experts, which in the latter case could lead to a higher risk of an innocent person being convicted for an untrained witness. © 2014 American Academy of Forensic Sciences.

Blind image quality assessment without training on human opinion scores

NASA Astrophysics Data System (ADS)

Mittal, Anish; Soundararajan, Rajiv; Muralidhar, Gautam S.; Bovik, Alan C.; Ghosh, Joydeep

2013-03-01

We propose a family of image quality assessment (IQA) models based on natural scene statistics (NSS), that can predict the subjective quality of a distorted image without reference to a corresponding distortionless image, and without any training results on human opinion scores of distorted images. These `completely blind' models compete well with standard non-blind image quality indices in terms of subjective predictive performance when tested on the large publicly available `LIVE' Image Quality database.

Quality measures in applications of image restoration.

PubMed

Kriete, A; Naim, M; Schafer, L

2001-01-01

We describe a new method for the estimation of image quality in image restoration applications. We demonstrate this technique on a simulated data set of fluorescent beads, in comparison with restoration by three different deconvolution methods. Both the number of iterations and a regularisation factor are varied to enforce changes in the resulting image quality. First, the data sets are directly compared by an accuracy measure. These values serve to validate the image quality descriptor, which is developed on the basis of optical information theory. This most general measure takes into account the spectral energies and the noise, weighted in a logarithmic fashion. It is demonstrated that this method is particularly helpful as a user-oriented method to control the output of iterative image restorations and to eliminate the guesswork in choosing a suitable number of iterations.

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT

PubMed Central

Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B

2014-01-01

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second (fps) were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction. PMID:24710978

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT.

PubMed

Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B

2014-05-01

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

Image aesthetic quality evaluation using convolution neural network embedded learning

NASA Astrophysics Data System (ADS)

Li, Yu-xin; Pu, Yuan-yuan; Xu, Dan; Qian, Wen-hua; Wang, Li-peng

2017-11-01

A way of embedded learning convolution neural network (ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale data but also score the image aesthetic quality. First, we chose Alexnet and VGG_S to compare for confirming which is more suitable for this image aesthetic quality evaluation task. Second, to further boost the image aesthetic quality classification performance, we employ the image content to train aesthetic quality classification models. But the training samples become smaller and only using once fine-tuning cannot make full use of the small-scale data set. Third, to solve the problem in second step, a way of using twice fine-tuning continually based on the aesthetic quality label and content label respective is proposed, the classification probability of the trained CNN models is used to evaluate the image aesthetic quality. The experiments are carried on the small-scale data set of Photo Quality. The experiment results show that the classification accuracy rates of our approach are higher than the existing image aesthetic quality evaluation approaches.

Cross-layer Energy Optimization Under Image Quality Constraints for Wireless Image Transmissions.

PubMed

Yang, Na; Demirkol, Ilker; Heinzelman, Wendi

2012-01-01

Wireless image transmission is critical in many applications, such as surveillance and environment monitoring. In order to make the best use of the limited energy of the battery-operated cameras, while satisfying the application-level image quality constraints, cross-layer design is critical. In this paper, we develop an image transmission model that allows the application layer (e.g., the user) to specify an image quality constraint, and optimizes the lower layer parameters of transmit power and packet length, to minimize the energy dissipation in image transmission over a given distance. The effectiveness of this approach is evaluated by applying the proposed energy optimization to a reference ZigBee system and a WiFi system, and also by comparing to an energy optimization study that does not consider any image quality constraint. Evaluations show that our scheme outperforms the default settings of the investigated commercial devices and saves a significant amount of energy at middle-to-large transmission distances.

Retinal Image Quality Assessment for Spaceflight-Induced Vision Impairment Study

NASA Technical Reports Server (NTRS)

Vu, Amanda Cadao; Raghunandan, Sneha; Vyas, Ruchi; Radhakrishnan, Krishnan; Taibbi, Giovanni; Vizzeri, Gianmarco; Grant, Maria; Chalam, Kakarla; Parsons-Wingerter, Patricia

2015-01-01

Long-term exposure to space microgravity poses significant risks for visual impairment. Evidence suggests such vision changes are linked to cephalad fluid shifts, prompting a need to directly quantify microgravity-induced retinal vascular changes. The quality of retinal images used for such vascular remodeling analysis, however, is dependent on imaging methodology. For our exploratory study, we hypothesized that retinal images captured using fluorescein imaging methodologies would be of higher quality in comparison to images captured without fluorescein. A semi-automated image quality assessment was developed using Vessel Generation Analysis (VESGEN) software and MATLAB® image analysis toolboxes. An analysis of ten images found that the fluorescein imaging modality provided a 36% increase in overall image quality (two-tailed p=0.089) in comparison to nonfluorescein imaging techniques.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

PubMed

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-12-01

Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

Imaging the Parasinus Region with a Third-Generation Dual-Source CT and the Effect of Tin Filtration on Image Quality and Radiation Dose.

PubMed

Lell, M M; May, M S; Brand, M; Eller, A; Buder, T; Hofmann, E; Uder, M; Wuest, W

2015-07-01

CT is the imaging technique of choice in the evaluation of midface trauma or inflammatory disease. We performed a systematic evaluation of scan protocols to optimize image quality and radiation exposure on third-generation dual-source CT. CT protocols with different tube voltage (70-150 kV), current (25-300 reference mAs), prefiltration, pitch value, and rotation time were systematically evaluated. All images were reconstructed with iterative reconstruction (Advanced Modeled Iterative Reconstruction, level 2). To individually compare results with otherwise identical factors, we obtained all scans on a frozen human head. Conebeam CT was performed for image quality and dose comparison with multidetector row CT. Delineation of important anatomic structures and incidental pathologic conditions in the cadaver head was evaluated. One hundred kilovolts with tin prefiltration demonstrated the best compromise between dose and image quality. The most dose-effective combination for trauma imaging was Sn100 kV/250 mAs (volume CT dose index, 2.02 mGy), and for preoperative sinus surgery planning, Sn100 kV/150 mAs (volume CT dose index, 1.22 mGy). "Sn" indicates an additional prefiltration of the x-ray beam with a tin filter to constrict the energy spectrum. Exclusion of sinonasal disease was possible with even a lower dose by using Sn100 kV/25 mAs (volume CT dose index, 0.2 mGy). High image quality at very low dose levels can be achieved by using a Sn100-kV protocol with iterative reconstruction. The effective dose is comparable with that of conventional radiography, and the high image quality at even lower radiation exposure favors multidetector row CT over conebeam CT. © 2015 by American Journal of Neuroradiology.

3D conditional generative adversarial networks for high-quality PET image estimation at low dose.

PubMed

Wang, Yan; Yu, Biting; Wang, Lei; Zu, Chen; Lalush, David S; Lin, Weili; Wu, Xi; Zhou, Jiliu; Shen, Dinggang; Zhou, Luping

2018-07-01

Positron emission tomography (PET) is a widely used imaging modality, providing insight into both the biochemical and physiological processes of human body. Usually, a full dose radioactive tracer is required to obtain high-quality PET images for clinical needs. This inevitably raises concerns about potential health hazards. On the other hand, dose reduction may cause the increased noise in the reconstructed PET images, which impacts the image quality to a certain extent. In this paper, in order to reduce the radiation exposure while maintaining the high quality of PET images, we propose a novel method based on 3D conditional generative adversarial networks (3D c-GANs) to estimate the high-quality full-dose PET images from low-dose ones. Generative adversarial networks (GANs) include a generator network and a discriminator network which are trained simultaneously with the goal of one beating the other. Similar to GANs, in the proposed 3D c-GANs, we condition the model on an input low-dose PET image and generate a corresponding output full-dose PET image. Specifically, to render the same underlying information between the low-dose and full-dose PET images, a 3D U-net-like deep architecture which can combine hierarchical features by using skip connection is designed as the generator network to synthesize the full-dose image. In order to guarantee the synthesized PET image to be close to the real one, we take into account of the estimation error loss in addition to the discriminator feedback to train the generator network. Furthermore, a concatenated 3D c-GANs based progressive refinement scheme is also proposed to further improve the quality of estimated images. Validation was done on a real human brain dataset including both the normal subjects and the subjects diagnosed as mild cognitive impairment (MCI). Experimental results show that our proposed 3D c-GANs method outperforms the benchmark methods and achieves much better performance than the state

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Validation of no-reference image quality index for the assessment of digital mammographic images

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Barufaldi, Bruno; Borges, Lucas R.; Gabarda, Salvador; Bakic, Predrag R.; Maidment, Andrew D. A.; Schiabel, Homero; Vieira, Marcelo A. C.

2016-03-01

To ensure optimal clinical performance of digital mammography, it is necessary to obtain images with high spatial resolution and low noise, keeping radiation exposure as low as possible. These requirements directly affect the interpretation of radiologists. The quality of a digital image should be assessed using objective measurements. In general, these methods measure the similarity between a degraded image and an ideal image without degradation (ground-truth), used as a reference. These methods are called Full-Reference Image Quality Assessment (FR-IQA). However, for digital mammography, an image without degradation is not available in clinical practice; thus, an objective method to assess the quality of mammograms must be performed without reference. The purpose of this study is to present a Normalized Anisotropic Quality Index (NAQI), based on the Rényi entropy in the pseudo-Wigner domain, to assess mammography images in terms of spatial resolution and noise without any reference. The method was validated using synthetic images acquired through an anthropomorphic breast software phantom, and the clinical exposures on anthropomorphic breast physical phantoms and patient's mammograms. The results reported by this noreference index follow the same behavior as other well-established full-reference metrics, e.g., the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Reductions of 50% on the radiation dose in phantom images were translated as a decrease of 4dB on the PSNR, 25% on the SSIM and 33% on the NAQI, evidencing that the proposed metric is sensitive to the noise resulted from dose reduction. The clinical results showed that images reduced to 53% and 30% of the standard radiation dose reported reductions of 15% and 25% on the NAQI, respectively. Thus, this index may be used in clinical practice as an image quality indicator to improve the quality assurance programs in mammography; hence, the proposed method reduces the subjectivity

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques

PubMed Central

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-01-01

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. PMID:28077898

Dose and diagnostic image quality in digital tomosynthesis imaging of facial bones in pediatrics

NASA Astrophysics Data System (ADS)

King, J. M.; Hickling, S.; Elbakri, I. A.; Reed, M.; Wrogemann, J.

2011-03-01

The purpose of this study was to evaluate the use of digital tomosynthesis (DT) for pediatric facial bone imaging. We compared the eye lens dose and diagnostic image quality of DT facial bone exams relative to digital radiography (DR) and computed tomography (CT), and investigated whether we could modify our current DT imaging protocol to reduce patient dose while maintaining sufficient diagnostic image quality. We measured the dose to the eye lens for all three modalities using high-sensitivity thermoluminescent dosimeters (TLDs) and an anthropomorphic skull phantom. To assess the diagnostic image quality of DT compared to the corresponding DR and CT images, we performed an observer study where the visibility of anatomical structures in the DT phantom images were rated on a four-point scale. We then acquired DT images at lower doses and had radiologists indicate whether the visibility of each structure was adequate for diagnostic purposes. For typical facial bone exams, we measured eye lens doses of 0.1-0.4 mGy for DR, 0.3-3.7 mGy for DT, and 26 mGy for CT. In general, facial bone structures were visualized better with DT then DR, and the majority of structures were visualized well enough to avoid the need for CT. DT imaging provides high quality diagnostic images of the facial bones while delivering significantly lower doses to the lens of the eye compared to CT. In addition, we found that by adjusting the imaging parameters, the DT effective dose can be reduced by up to 50% while maintaining sufficient image quality.

Quality assurance of multiport image-guided minimally invasive surgery at the lateral skull base.

PubMed

Nau-Hermes, Maria; Schmitt, Robert; Becker, Meike; El-Hakimi, Wissam; Hansen, Stefan; Klenzner, Thomas; Schipper, Jörg

2014-01-01

For multiport image-guided minimally invasive surgery at the lateral skull base a quality management is necessary to avoid the damage of closely spaced critical neurovascular structures. So far there is no standardized method applicable independently from the surgery. Therefore, we adapt a quality management method, the quality gates (QG), which is well established in, for example, the automotive industry and apply it to multiport image-guided minimally invasive surgery. QG divide a process into different sections. Passing between sections can only be achieved if previously defined requirements are fulfilled which secures the process chain. An interdisciplinary team of otosurgeons, computer scientists, and engineers has worked together to define the quality gates and the corresponding criteria that need to be fulfilled before passing each quality gate. In order to evaluate the defined QG and their criteria, the new surgery method was applied with a first prototype at a human skull cadaver model. We show that the QG method can ensure a safe multiport minimally invasive surgical process at the lateral skull base. Therewith, we present an approach towards the standardization of quality assurance of surgical processes.

Quality Assurance of Multiport Image-Guided Minimally Invasive Surgery at the Lateral Skull Base

PubMed Central

Nau-Hermes, Maria; Schmitt, Robert; Becker, Meike; El-Hakimi, Wissam; Hansen, Stefan; Klenzner, Thomas; Schipper, Jörg

2014-01-01

For multiport image-guided minimally invasive surgery at the lateral skull base a quality management is necessary to avoid the damage of closely spaced critical neurovascular structures. So far there is no standardized method applicable independently from the surgery. Therefore, we adapt a quality management method, the quality gates (QG), which is well established in, for example, the automotive industry and apply it to multiport image-guided minimally invasive surgery. QG divide a process into different sections. Passing between sections can only be achieved if previously defined requirements are fulfilled which secures the process chain. An interdisciplinary team of otosurgeons, computer scientists, and engineers has worked together to define the quality gates and the corresponding criteria that need to be fulfilled before passing each quality gate. In order to evaluate the defined QG and their criteria, the new surgery method was applied with a first prototype at a human skull cadaver model. We show that the QG method can ensure a safe multiport minimally invasive surgical process at the lateral skull base. Therewith, we present an approach towards the standardization of quality assurance of surgical processes. PMID:25105146

Dose reduction and image quality optimizations in CT of pediatric and adult patients: phantom studies

NASA Astrophysics Data System (ADS)

Jeon, P.-H.; Lee, C.-L.; Kim, D.-H.; Lee, Y.-J.; Jeon, S.-S.; Kim, H.-J.

2014-03-01

Multi-detector computed tomography (MDCT) can be used to easily and rapidly perform numerous acquisitions, possibly leading to a marked increase in the radiation dose to individual patients. Technical options dedicated to automatically adjusting the acquisition parameters according to the patient's size are of specific interest in pediatric radiology. A constant tube potential reduction can be achieved for adults and children, while maintaining a constant detector energy fluence. To evaluate radiation dose, the weighted CT dose index (CTDIw) was calculated based on the CT dose index (CTDI) measured using an ion chamber, and image noise and image contrast were measured from a scanned image to evaluate image quality. The dose-weighted contrast-to-noise ratio (CNRD) was calculated from the radiation dose, image noise, and image contrast measured from a scanned image. The noise derivative (ND) is a quality index for dose efficiency. X-ray spectra with tube voltages ranging from 80 to 140 kVp were used to compute the average photon energy. Image contrast and the corresponding contrast-to-noise ratio (CNR) were determined for lesions of soft tissue, muscle, bone, and iodine relative to a uniform water background, as the iodine contrast increases at lower energy (i.e., k-edge of iodine is 33 keV closer to the beam energy) using mixed water-iodine contrast normalization (water 0, iodine 25, 100, 200, and 1000 HU, respectively). The proposed values correspond to high quality images and can be reduced if only high-contrast organs are assessed. The potential benefit of lowering the tube voltage is an improved CNRD, resulting in a lower radiation dose and optimization of image quality. Adjusting the tube potential in abdominal CT would be useful in current pediatric radiography, where the choice of X-ray techniques generally takes into account the size of the patient as well as the need to balance the conflicting requirements of diagnostic image quality and radiation dose

Imaging quality evaluation method of pixel coupled electro-optical imaging system

NASA Astrophysics Data System (ADS)

He, Xu; Yuan, Li; Jin, Chunqi; Zhang, Xiaohui

2017-09-01

With advancements in high-resolution imaging optical fiber bundle fabrication technology, traditional photoelectric imaging system have become ;flexible; with greatly reduced volume and weight. However, traditional image quality evaluation models are limited by the coupling discrete sampling effect of fiber-optic image bundles and charge-coupled device (CCD) pixels. This limitation substantially complicates the design, optimization, assembly, and evaluation image quality of the coupled discrete sampling imaging system. Based on the transfer process of grayscale cosine distribution optical signal in the fiber-optic image bundle and CCD, a mathematical model of coupled modulation transfer function (coupled-MTF) is established. This model can be used as a basis for following studies on the convergence and periodically oscillating characteristics of the function. We also propose the concept of the average coupled-MTF, which is consistent with the definition of traditional MTF. Based on this concept, the relationships among core distance, core layer radius, and average coupled-MTF are investigated.

[Quality control of laser imagers].

PubMed

Winkelbauer, F; Ammann, M; Gerstner, N; Imhof, H

1992-11-01

Multiformat imagers based on laser systems are used for documentation in an increasing number of investigations. The specific problems of quality control are explained and the persistence of film processing in these imager systems of different configuration with (Machine 1: 3M-Laser-Imager-Plus M952 with connected 3M Film-Processor, 3M-Film IRB, X-Rax Chemical Mixer 3M-XPM, 3M-Developer and Fixer) or without (Machine 2: 3M-Laser-Imager-Plus M952 with separate DuPont-Cronex Film-processor, Kodak IR-Film, Kodak Automixer, Kodak-Developer and Fixer) connected film processing unit are investigated. In our checking based on DIN 6868 and ONORM S 5240 we found persistence of film processing in the equipment with directly adapted film processing unit according to DIN and ONORM. The checking of film persistence as demanded by DIN 6868 in these equipment could therefore be performed in longer periods. Systems with conventional darkroom processing comparatively show plain increased fluctuation, and hence the demanded daily control is essential to guarantee appropriate reaction and constant quality of documentation.

Deep supervised dictionary learning for no-reference image quality assessment

NASA Astrophysics Data System (ADS)

Huang, Yuge; Liu, Xuesong; Tian, Xiang; Zhou, Fan; Chen, Yaowu; Jiang, Rongxin

2018-03-01

We propose a deep convolutional neural network (CNN) for general no-reference image quality assessment (NR-IQA), i.e., accurate prediction of image quality without a reference image. The proposed model consists of three components such as a local feature extractor that is a fully CNN, an encoding module with an inherent dictionary that aggregates local features to output a fixed-length global quality-aware image representation, and a regression module that maps the representation to an image quality score. Our model can be trained in an end-to-end manner, and all of the parameters, including the weights of the convolutional layers, the dictionary, and the regression weights, are simultaneously learned from the loss function. In addition, the model can predict quality scores for input images of arbitrary sizes in a single step. We tested our method on commonly used image quality databases and showed that its performance is comparable with that of state-of-the-art general-purpose NR-IQA algorithms.

Clinical image quality evaluation for panoramic radiography in Korean dental clinics

PubMed Central

Choi, Bo-Ram; Choi, Da-Hye; Huh, Kyung-Hoe; Yi, Won-Jin; Heo, Min-Suk; Choi, Soon-Chul; Bae, Kwang-Hak

2012-01-01

Purpose The purpose of this study was to investigate the level of clinical image quality of panoramic radiographs and to analyze the parameters that influence the overall image quality. Materials and Methods Korean dental clinics were asked to provide three randomly selected panoramic radiographs. An oral and maxillofacial radiology specialist evaluated those images using our self-developed Clinical Image Quality Evaluation Chart. Three evaluators classified the overall image quality of the panoramic radiographs and evaluated the causes of imaging errors. Results A total of 297 panoramic radiographs were collected from 99 dental hospitals and clinics. The mean of the scores according to the Clinical Image Quality Evaluation Chart was 79.9. In the classification of the overall image quality, 17 images were deemed 'optimal for obtaining diagnostic information,' 153 were 'adequate for diagnosis,' 109 were 'poor but diagnosable,' and nine were 'unrecognizable and too poor for diagnosis'. The results of the analysis of the causes of the errors in all the images are as follows: 139 errors in the positioning, 135 in the processing, 50 from the radiographic unit, and 13 due to anatomic abnormality. Conclusion Panoramic radiographs taken at local dental clinics generally have a normal or higher-level image quality. Principal factors affecting image quality were positioning of the patient and image density, sharpness, and contrast. Therefore, when images are taken, the patient position should be adjusted with great care. Also, standardizing objective criteria of image density, sharpness, and contrast is required to evaluate image quality effectively. PMID:23071969

Image quality prediction - An aid to the Viking lander imaging investigation on Mars

NASA Technical Reports Server (NTRS)

Huck, F. O.; Wall, S. D.

1976-01-01

Image quality criteria and image quality predictions are formulated for the multispectral panoramic cameras carried by the Viking Mars landers. Image quality predictions are based on expected camera performance, Mars surface radiance, and lighting and viewing geometry (fields of view, Mars lander shadows, solar day-night alternation), and are needed in diagnosis of camera performance, in arriving at a preflight imaging strategy, and revision of that strategy should the need arise. Landing considerations, camera control instructions, camera control logic, aspects of the imaging process (spectral response, spatial response, sensitivity), and likely problems are discussed. Major concerns include: degradation of camera response by isotope radiation, uncertainties in lighting and viewing geometry and in landing site local topography, contamination of camera window by dust abrasion, and initial errors in assigning camera dynamic ranges (gains and offsets).

Evaluating imaging quality between different ghost imaging systems based on the coherent-mode representation

NASA Astrophysics Data System (ADS)

Shen, Qian; Bai, Yanfeng; Shi, Xiaohui; Nan, Suqin; Qu, Lijie; Li, Hengxing; Fu, Xiquan

2017-07-01

The difference in imaging quality between different ghost imaging schemes is studied by using coherent-mode representation of partially coherent fields. It is shown that the difference mainly relies on the distribution changes of the decomposition coefficients of the object imaged when the light source is fixed. For a new-designed imaging scheme, we only need to give the distribution of the decomposition coefficients and compare them with that of the existing imaging system, thus one can predict imaging quality. By choosing several typical ghost imaging systems, we theoretically and experimentally verify our results.

Subjective evaluation of compressed image quality

NASA Astrophysics Data System (ADS)

Lee, Heesub; Rowberg, Alan H.; Frank, Mark S.; Choi, Hyung-Sik; Kim, Yongmin

1992-05-01

Lossy data compression generates distortion or error on the reconstructed image and the distortion becomes visible as the compression ratio increases. Even at the same compression ratio, the distortion appears differently depending on the compression method used. Because of the nonlinearity of the human visual system and lossy data compression methods, we have evaluated subjectively the quality of medical images compressed with two different methods, an intraframe and interframe coding algorithms. The evaluated raw data were analyzed statistically to measure interrater reliability and reliability of an individual reader. Also, the analysis of variance was used to identify which compression method is better statistically, and from what compression ratio the quality of a compressed image is evaluated as poorer than that of the original. Nine x-ray CT head images from three patients were used as test cases. Six radiologists participated in reading the 99 images (some were duplicates) compressed at four different compression ratios, original, 5:1, 10:1, and 15:1. The six readers agree more than by chance alone and their agreement was statistically significant, but there were large variations among readers as well as within a reader. The displacement estimated interframe coding algorithm is significantly better in quality than that of the 2-D block DCT at significance level 0.05. Also, 10:1 compressed images with the interframe coding algorithm do not show any significant differences from the original at level 0.05.

A qualitative and quantitative analysis of radiation dose and image quality of computed tomography images using adaptive statistical iterative reconstruction

PubMed Central

Mail, Noor; Shamy, Abdulrahman M.; Alghamdi, Suliman; Saoudi, Abdelhamid

2016-01-01

Image quality is a key issue in radiology, particularly in a clinical setting where it is important to achieve accurate diagnoses while minimizing radiation dose. Some computed tomography (CT) manufacturers have introduced algorithms that claim significant dose reduction. In this study, we assessed CT image quality produced by two reconstruction algorithms provided with GE Healthcare's Discovery 690 Elite positron emission tomography (PET) CT scanner. Image quality was measured for images obtained at various doses with both conventional filtered back‐projection (FBP) and adaptive statistical iterative reconstruction (ASIR) algorithms. A standard CT dose index (CTDI) phantom and a pencil ionization chamber were used to measure the CT dose at 120 kVp and an exposure of 260 mAs. Image quality was assessed using two phantoms. CT images of both phantoms were acquired at tube voltage (kV) of 120 with exposures ranging from 25 mAs to 400 mAs. Images were reconstructed using FBP and ASIR ranging from 10% to 100%, then analyzed for noise, low‐contrast detectability, contrast‐to‐noise ratio (CNR), and modulation transfer function (MTF). Noise was 4.6 HU in water phantom images acquired at 260 mAs/FBP 120 kV and 130 mAs/50% ASIR 120 kV. The large objects (frequency<7 lp/cm) retained fairly acceptable image quality at 130 mAs/50% ASIR, compared to 260 mAs/FBP. The application of ASIR for small objects (frequency>7 lp/cm) showed poor visibility compared to FBP at 260 mAs and even worse for images acquired at less than 130 mAs. ASIR blending more than 50% at low dose tends to reduce contrast of small objects (frequency>7 lp/cm). We concluded that dose reduction and ASIR should be applied with close attention if the objects to be detected or diagnosed are small (frequency>7 lp/cm). Further investigations are required to correlate the small objects (frequency>7 lp/cm) to patient anatomy and clinical diagnosis. PACS number(s): 87.57.‐s, 87.57.C, 87.57.cf, 87

Does Teacher Quality Affect Student Achievement? An Empirical Study in Indonesia

ERIC Educational Resources Information Center

Sirait, Swando

2016-01-01

The objective of this study is to examine the relationship between teacher qualities in relation to student achievement in Indonesia. Teacher quality in this study defines as teacher evaluation score, in the areas of professional and pedagogic competency. The result of this study consonant to previous study that teacher quality, in term of teacher…

Impact of image quality on OCT angiography based quantitative measurements.

PubMed

Al-Sheikh, Mayss; Ghasemi Falavarjani, Khalil; Akil, Handan; Sadda, SriniVas R

2017-01-01

To study the impact of image quality on quantitative measurements and the frequency of segmentation error with optical coherence tomography angiography (OCTA). Seventeen eyes of 10 healthy individuals were included in this study. OCTA was performed using a swept-source device (Triton, Topcon). Each subject underwent three scanning sessions 1-2 min apart; the first two scans were obtained under standard conditions and for the third session, the image quality index was reduced using application of a topical ointment. En face OCTA images of the retinal vasculature were generated using the default segmentation for the superficial and deep retinal layer (SRL, DRL). Intraclass correlation coefficient (ICC) was used as a measure for repeatability. The frequency of segmentation error, motion artifact, banding artifact and projection artifact was also compared among the three sessions. The frequency of segmentation error, and motion artifact was statistically similar between high and low image quality sessions (P = 0.707, and P = 1 respectively). However, the frequency of projection and banding artifact was higher with a lower image quality. The vessel density in the SRL was highly repeatable in the high image quality sessions (ICC = 0.8), however, the repeatability was low, comparing the high and low image quality measurements (ICC = 0.3). In the DRL, the repeatability of the vessel density measurements was fair in the high quality sessions (ICC = 0.6 and ICC = 0.5, with and without automatic artifact removal, respectively) and poor comparing high and low image quality sessions (ICC = 0.3 and ICC = 0.06, with and without automatic artifact removal, respectively). The frequency of artifacts is higher and the repeatability of the measurements is lower with lower image quality. The impact of image quality index should be always considered in OCTA based quantitative measurements.

Scale Control and Quality Management of Printed Image Parameters

NASA Astrophysics Data System (ADS)

Novoselskaya, O. A.; Kolesnikov, V. L.; Solov'eva, T. V.; Nagornova, I. V.; Babluyk, E. B.; Trapeznikova, O. V.

2017-06-01

The article provides a comparison of the main valuation techniques for a regulated parameter of printability of the offset paper by current standards GOST 24356 and ISO 3783: 2006. The results of development and implementation of a complex test scale for management and control the quality of printed production are represented. The estimation scale is introduced. It includes normalized parameters of print optical density, print uniformity, picking out speed, the value of dot gain, print contrast with the added criteria of minimizing microtexts, a paper slip, resolution threshold and effusing ability of paper surface. The results of analysis allow directionally form surface properties of the substrate to facilitate achieving the required quality of the printed image parameters, i. e. optical density of a print at a predetermined level not less than 1.3, the print uniformity with minimal deviation of dot gain about the order of 10 per cents.

Review of Image Quality Measures for Solar Imaging

NASA Astrophysics Data System (ADS)

Popowicz, Adam; Radlak, Krystian; Bernacki, Krzysztof; Orlov, Valeri

2017-12-01

Observations of the solar photosphere from the ground encounter significant problems caused by Earth's turbulent atmosphere. Before image reconstruction techniques can be applied, the frames obtained in the most favorable atmospheric conditions (the so-called lucky frames) have to be carefully selected. However, estimating the quality of images containing complex photospheric structures is not a trivial task, and the standard routines applied in nighttime lucky imaging observations are not applicable. In this paper we evaluate 36 methods dedicated to the assessment of image quality, which were presented in the literature over the past 40 years. We compare their effectiveness on simulated solar observations of both active regions and granulation patches, using reference data obtained by the Solar Optical Telescope on the Hinode satellite. To create images that are affected by a known degree of atmospheric degradation, we employed the random wave vector method, which faithfully models all the seeing characteristics. The results provide useful information about the method performances, depending on the average seeing conditions expressed by the ratio of the telescope's aperture to the Fried parameter, D/r0. The comparison identifies three methods for consideration by observers: Helmli and Scherer's mean, the median filter gradient similarity, and the discrete cosine transform energy ratio. While the first method requires less computational effort and can be used effectively in virtually any atmospheric conditions, the second method shows its superiority at good seeing (D/r0<4). The third method should mainly be considered for the post-processing of strongly blurred images.

Dynamic flat panel detector versus image intensifier in cardiac imaging: dose and image quality

NASA Astrophysics Data System (ADS)

Vano, E.; Geiger, B.; Schreiner, A.; Back, C.; Beissel, J.

2005-12-01

The practical aspects of the dosimetric and imaging performance of a digital x-ray system for cardiology procedures were evaluated. The system was configured with an image intensifier (II) and later upgraded to a dynamic flat panel detector (FD). Entrance surface air kerma (ESAK) to phantoms of 16, 20, 24 and 28 cm of polymethyl methacrylate (PMMA) and the image quality of a test object were measured. Images were evaluated directly on the monitor and with numerical methods (noise and signal-to-noise ratio). Information contained in the DICOM header for dosimetry audit purposes was also tested. ESAK values per frame (or kerma rate) for the most commonly used cine and fluoroscopy modes for different PMMA thicknesses and for field sizes of 17 and 23 cm for II, and 20 and 25 cm for FD, produced similar results in the evaluated system with both technologies, ranging between 19 and 589 µGy/frame (cine) and 5 and 95 mGy min-1 (fluoroscopy). Image quality for these dose settings was better for the FD version. The 'study dosimetric report' is comprehensive, and its numerical content is sufficiently accurate. There is potential in the future to set those systems with dynamic FD to lower doses than are possible in the current II versions, especially for digital cine runs, or to benefit from improved image quality.

Readout-Segmented Echo-Planar Imaging in Diffusion-Weighted MR Imaging in Breast Cancer: Comparison with Single-Shot Echo-Planar Imaging in Image Quality

PubMed Central

Kim, Yun Ju; Kang, Bong Joo; Park, Chang Suk; Kim, Hyeon Sook; Son, Yo Han; Porter, David Andrew; Song, Byung Joo

2014-01-01

Objective The purpose of this study was to compare the image quality of standard single-shot echo-planar imaging (ss-EPI) and that of readout-segmented EPI (rs-EPI) in patients with breast cancer. Materials and Methods Seventy-one patients with 74 breast cancers underwent both ss-EPI and rs-EPI. For qualitative comparison of image quality, three readers independently assessed the two sets of diffusion-weighted (DW) images. To evaluate geometric distortion, a comparison was made between lesion lengths derived from contrast enhanced MR (CE-MR) images and those obtained from the corresponding DW images. For assessment of image parameters, signal-to-noise ratio (SNR), lesion contrast, and contrast-to-noise ratio (CNR) were calculated. Results The rs-EPI was superior to ss-EPI in most criteria regarding the qualitative image quality. Anatomical structure distinction, delineation of the lesion, ghosting artifact, and overall image quality were significantly better in rs-EPI. Regarding the geometric distortion, lesion length on ss-EPI was significantly different from that of CE-MR, whereas there were no significant differences between CE-MR and rs-EPI. The rs-EPI was superior to ss-EPI in SNR and CNR. Conclusion Readout-segmented EPI is superior to ss-EPI in the aspect of image quality in DW MR imaging of the breast. PMID:25053898

Topological image texture analysis for quality assessment

NASA Astrophysics Data System (ADS)

Asaad, Aras T.; Rashid, Rasber Dh.; Jassim, Sabah A.

2017-05-01

Image quality is a major factor influencing pattern recognition accuracy and help detect image tampering for forensics. We are concerned with investigating topological image texture analysis techniques to assess different type of degradation. We use Local Binary Pattern (LBP) as a texture feature descriptor. For any image construct simplicial complexes for selected groups of uniform LBP bins and calculate persistent homology invariants (e.g. number of connected components). We investigated image quality discriminating characteristics of these simplicial complexes by computing these models for a large dataset of face images that are affected by the presence of shadows as a result of variation in illumination conditions. Our tests demonstrate that for specific uniform LBP patterns, the number of connected component not only distinguish between different levels of shadow effects but also help detect the infected regions as well.

Image Quality Performance Measurement of the microPET Focus 120

NASA Astrophysics Data System (ADS)

Ballado, Fernando Trejo; López, Nayelli Ortega; Flores, Rafael Ojeda; Ávila-Rodríguez, Miguel A.

2010-12-01

The aim of this work is to evaluate the characteristics involved in the image reconstruction of the microPET Focus 120. For this evaluation were used two different phantoms; a miniature hot-rod Derenzo phantom and a National Electrical Manufacturers Association (NEMA) NU4-2008 image quality (IQ) phantom. The best image quality was obtained when using OSEM3D as the reconstruction method reaching a spatial resolution of 1.5 mm with the Derenzo phantom filled with 18F. Image quality test results indicate a superior image quality for the Focus 120 when compared to previous microPET models.

A study of image quality for radar image processing. [synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

King, R. W.; Kaupp, V. H.; Waite, W. P.; Macdonald, H. C.

1982-01-01

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics.

The use of the general image quality equation in the design and evaluation of imaging systems

NASA Astrophysics Data System (ADS)

Cota, Steve A.; Florio, Christopher J.; Duvall, David J.; Leon, Michael A.

2009-08-01

The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. The National Imagery Interpretability Rating Scale (NIIRS) is a useful measure of image quality, because, by characterizing the overall interpretability of an image, it combines into one metric those contributors to image quality to which a human interpreter is most sensitive. The main drawback to using a NIIRS rating as a measure of image quality in engineering trade studies is the fact that it is tied to the human observer and cannot be predicted from physical principles and engineering parameters alone. The General Image Quality Equation (GIQE) of Leachtenauer et al. 1997 [Appl. Opt. 36, 8322-8328 (1997)] is a regression of actual image analyst NIIRS ratings vs. readily calculable engineering metrics, and provides a mechanism for using the expected NIIRS rating of an imaging system in the design and evaluation process. In this paper, we will discuss how we use the GIQE in conjunction with The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) to evaluate imager designs, taking a hypothetical high resolution commercial imaging system as an example.

New opportunities for quality enhancing of images captured by passive THz camera

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2014-10-01

As it is well-known, the passive THz camera allows seeing concealed object without contact with a person and this camera is non-dangerous for a person. Obviously, efficiency of using the passive THz camera depends on its temperature resolution. This characteristic specifies possibilities of the detection for concealed object: minimal size of the object; maximal distance of the detection; image quality. Computer processing of the THz image may lead to many times improving of the image quality without any additional engineering efforts. Therefore, developing of modern computer code for its application to THz images is urgent problem. Using appropriate new methods one may expect such temperature resolution which will allow to see banknote in pocket of a person without any real contact. Modern algorithms for computer processing of THz images allow also to see object inside the human body using a temperature trace on the human skin. This circumstance enhances essentially opportunity of passive THz camera applications for counterterrorism problems. We demonstrate opportunities, achieved at present time, for the detection both of concealed objects and of clothes components due to using of computer processing of images captured by passive THz cameras, manufactured by various companies. Another important result discussed in the paper consists in observation of both THz radiation emitted by incandescent lamp and image reflected from ceramic floorplate. We consider images produced by THz passive cameras manufactured by Microsemi Corp., and ThruVision Corp., and Capital Normal University (Beijing, China). All algorithms for computer processing of the THz images under consideration in this paper were developed by Russian part of author list. Keywords: THz wave, passive imaging camera, computer processing, security screening, concealed and forbidden objects, reflected image, hand seeing, banknote seeing, ceramic floorplate, incandescent lamp.

Comparison of image quality, myocardial perfusion, and LV function between standard imaging and single-injection ultra-low-dose imaging using a high-efficiency SPECT camera: the MILLISIEVERT study

PubMed Central

Einstein, Andrew J.; Blankstein, Ron; Andrews, Howard; Fish, Mathews; Padgett, Richard; Hayes, Sean W.; Friedman, John D.; Qureshi, Mehreen; Rakotoarivelo, Harivony; Slomka, Piotr; Nakazato, Ryo; Bokhari, Sabahat; Di Carli, Marcello; Berman, Daniel S.

2015-01-01

SPECT myocardial perfusion imaging (MPI) plays a central role in coronary artery disease diagnosis; but concerns exist regarding its radiation burden. Compared to standard Anger-SPECT (A-SPECT) cameras, new high-efficiency (HE) cameras with specialized collimators and solid-state cadmium-zinc-telluride detectors offer potential to maintain image quality (IQ), while reducing administered activity and thus radiation dose to patients. No previous study has compared IQ, interpretation, total perfusion deficit (TPD), or ejection fraction (EF) in patients receiving both ultra-low-dose (ULD) imaging on a HE-SPECT camera and standard low-dose (SLD) A-SPECT imaging. Methods We compared ULD-HE-SPECT to SLD-A-SPECT imaging by dividing the rest dose in 101 patients at 3 sites scheduled to undergo clinical A-SPECT MPI using a same day rest/stress Tc-99m protocol. Patients received HE-SPECT imaging following an initial ~130 MBq (3.5mCi) dose, and SLD-A-SPECT imaging following the remainder of the planned dose. Images were scored visually by 2 blinded readers for IQ and summed rest score (SRS). TPD and EF were assessed quantitatively. Results Mean activity was 134 MBq (3.62 mCi) for ULD-HE-SPECT (effective dose 1.15 mSv) and 278 MBq (7.50 mCi, 2.39 mSv) for SLD-A-SPECT. Overall IQ was superior for ULD-HE-SPECT (p<0.0001), with twice as many studies graded excellent quality. Extracardiac activity and overall perfusion assessment were similar. Between-method correlations were high for SRS (r=0.87), TPD (r=0.91), and EF (r=0.88). Conclusion ULD-HE-SPECT rest imaging correlates highly with SLD-A-SPECT. It has improved image quality, comparable extracardiac activity, and achieves radiation dose reduction to 1 mSv for a single injection. PMID:24982439

Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images

NASA Astrophysics Data System (ADS)

Rector, Travis A.; Levay, Zoltan G.; Frattare, Lisa M.; English, Jayanne; Pu'uohau-Pummill, Kirk

2007-02-01

The quality of modern astronomical data and the agility of current image-processing software enable the visualization of data in a way that exceeds the traditional definition of an astronomical image. Two developments in particular have led to a fundamental change in how astronomical images can be assembled. First, the availability of high-quality multiwavelength and narrowband data allow for images that do not correspond to the wavelength sensitivity of the human eye, thereby introducing ambiguity in the usage and interpretation of color. Second, many image-processing software packages now use a layering metaphor that allows for any number of astronomical data sets to be combined into a color image. With this technique, images with as many as eight data sets have been produced. Each data set is intensity-scaled and colorized independently, creating an immense parameter space that can be used to assemble the image. Since such images are intended for data visualization, scaling and color schemes must be chosen that best illustrate the science. A practical guide is presented on how to use the layering metaphor to generate publication-ready astronomical images from as many data sets as desired. A methodology is also given on how to use intensity scaling, color, and composition to create contrasts in an image that highlight the scientific detail. Examples of image creation are discussed.

The Relationship between University Students' Academic Achievement and Perceived Organizational Image

ERIC Educational Resources Information Center

Polat, Soner

2011-01-01

The purpose of present study was to determine the relationship between university students' academic achievement and perceived organizational image. The sample of the study was the senior students at the faculties and vocational schools in Umuttepe Campus at Kocaeli University. Because the development of organizational image is a long process, the…

Achieving interlocking nails without using an image intensifier

PubMed Central

Ogunlusi, Johnson D.; Ine, Henry R.

2006-01-01

Interlocking nails are commonly performed using an image intensifier. These are expensive and are not readily available in most resource-poor countries of the world. The aim of this study was to achieve interlocking nailing without the use of an image intensifier. This is a prospective descriptive analysis of 40 consecutive cases seen with shaft fractures of the humerus, femur, and tibia. Fracture fixation was done using Surgical Implant Generation Network (SIGN) nails. Forty limbs in 34 patients were studied. There were 12 females and 22 males, giving a ratio of 1:2. The mean age (years) was 35.75±13.16 and the range was 17–70 years. The studied bones were: humerus 10%, femur 65%, and tibia 25%. The fracture lines were: transverse 40%, oblique 15%, and communited 45%. Fracture grades were: closed 90%, grade I, 5%, grade II, 2.5%, and grade IIIA, 2.5%. Surgical approaches were: antegrade 62.5% and retrograde 37.5%. Indications for fixation were: recent fracture 92.5%, non-union 5%, and malunion 3%. Methods of reductions were: open 85% and closed 15%. The mean follow-up period (years) was 1.50±0.78. The union time averaged 3 months. Complication was mainly screw loosening due to severe osteoporoses in one case. It is, therefore, concluded that, with the aid of external jigs and slot finders, interlocking can be achieved without an image intensifier. PMID:17039384

Assessing microscope image focus quality with deep learning.

PubMed

Yang, Samuel J; Berndl, Marc; Michael Ando, D; Barch, Mariya; Narayanaswamy, Arunachalam; Christiansen, Eric; Hoyer, Stephan; Roat, Chris; Hung, Jane; Rueden, Curtis T; Shankar, Asim; Finkbeiner, Steven; Nelson, Philip

2018-03-15

Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unbiased image dataset. Complicating this task is the fact that image focus quality is only well-defined in foreground regions of images, and as a result, most previous approaches only enable a computation of the relative difference in quality between two or more images, rather than an absolute measure of quality. We present a deep neural network model capable of predicting an absolute measure of image focus on a single image in isolation, without any user-specified parameters. The model operates at the image-patch level, and also outputs a measure of prediction certainty, enabling interpretable predictions. The model was trained on only 384 in-focus Hoechst (nuclei) stain images of U2OS cells, which were synthetically defocused to one of 11 absolute defocus levels during training. The trained model can generalize on previously unseen real Hoechst stain images, identifying the absolute image focus to within one defocus level (approximately 3 pixel blur diameter difference) with 95% accuracy. On a simpler binary in/out-of-focus classification task, the trained model outperforms previous approaches on both Hoechst and Phalloidin (actin) stain images (F-scores of 0.89 and 0.86, respectively over 0.84 and 0.83), despite only having been presented Hoechst stain images during training. Lastly, we observe qualitatively that the model generalizes to two additional stains, Hoechst and Tubulin, of an unseen cell type (Human MCF-7) acquired on a different instrument. Our deep neural network enables classification of out-of-focus microscope images with both higher accuracy and greater precision than previous approaches via interpretable patch-level focus and certainty predictions. The use of

Assessment of CT image quality using a Bayesian approach

NASA Astrophysics Data System (ADS)

Reginatto, M.; Anton, M.; Elster, C.

2017-08-01

One of the most promising approaches for evaluating CT image quality is task-specific quality assessment. This involves a simplified version of a clinical task, e.g. deciding whether an image belongs to the class of images that contain the signature of a lesion or not. Task-specific quality assessment can be done by model observers, which are mathematical procedures that carry out the classification task. The most widely used figure of merit for CT image quality is the area under the ROC curve (AUC), a quantity which characterizes the performance of a given model observer. In order to estimate AUC from a finite sample of images, different approaches from classical statistics have been suggested. The goal of this paper is to introduce task-specific quality assessment of CT images to metrology and to propose a novel Bayesian estimation of AUC for the channelized Hotelling observer (CHO) applied to the task of detecting a lesion at a known image location. It is assumed that signal-present and signal-absent images follow multivariate normal distributions with the same covariance matrix. The Bayesian approach results in a posterior distribution for the AUC of the CHO which provides in addition a complete characterization of the uncertainty of this figure of merit. The approach is illustrated by its application to both simulated and experimental data.

Helical prospective ECG-gating in cardiac computed tomography: radiation dose and image quality.

PubMed

DeFrance, Tony; Dubois, Eric; Gebow, Dan; Ramirez, Alex; Wolf, Florian; Feuchtner, Gudrun M

2010-01-01

Helical prospective ECG-gating (pECG) may reduce radiation dose while maintaining the advantages of helical image acquisition for coronary computed tomography angiography (CCTA). Aim of this study was to evaluate helical pECG-gating in CCTA in regards to radiation dose and image quality. 86 patients undergoing 64-multislice CCTA were enrolled. pECG-gating was performed in patients with regular heart rates (HR) < 65 bpm; with the gating window set at 70-85% of the cardiac cycle. All patients received oral and some received additional IV beta-blockers to achieve HR < 65 bpm. In patients with higher or irregular HR, or for functional evaluation, retrospective ECG-gating (rECG) was performed. The average X-ray dose was estimated from the dose length product. Each arterial segment (modified AHA/ACC 17-segment-model) was evaluated on a 4-point image quality scale (4 = excellent; 3 = good, mild artefact; 2 = acceptable, some artefact, 1 = uninterpretable). pECG-gating was applied in 57 patients, rECG-gating in 29 patients. There was no difference in age, gender, body mass index, scan length or tube output settings between both groups. HR in the pECG-group was 54.7 bpm (range, 43-64). The effective radiation dose was significantly lower for patients scanned with pECG-gating with mean 6.9 mSv +/- 1.9 (range, 2.9-10.7) compared to rECG with 16.9 mSv +/- 4.1 (P < 0.001), resulting in a mean dose reduction of 59.2%. For pECG-gating, out of 969 coronary segments, 99.3% were interpretable. Image quality was excellent in 90.2%, good in 7.8%, acceptable in 1.3% and non-interpretable in 0.7% (n = 7 segments). For patients with steady heart rates <65 bpm, helical prospective ECG-gating can significantly lower the radiation dose while maintaining high image quality.

Derivation of the scan time requirement for maintaining a consistent PET image quality

NASA Astrophysics Data System (ADS)

Kim, Jin Su; Lee, Jae Sung; Kim, Seok-Ki

2015-05-01

Objectives: the image quality of PET for larger patients is relatively poor, even though the injection dose is optimized considering the NECR characteristics of the PET scanner. This poor image quality is due to the lower level of maximum NECR that can be achieved in these large patients. The aim of this study was to optimize the PET scan time to obtain a consistent PET image quality regardless of the body size, based on the relationship between the patient specific NECR (pNECR) and body weight. Methods: eighty patients (M/F=53/27, body weight: 059 ± 1 kg) underwent whole-body FDG PET scans using a Philips GEMINI GS PET/CT scanner after an injection of 0.14 mCi/kg FDG. The relationship between the scatter fraction (SF) and body weight was determined by repeated Monte Carlo simulations using a NEMA scatter phantom, the size of which varied according to the relationship between the abdominal circumference and body weight. Using this information, the pNECR was calculated from the prompt and delayed PET sinograms to obtain the prediction equation of NECR vs. body weight. The time scaling factor (FTS) for the scan duration was finally derived to make PET images with equivalent SNR levels. Results: the SF and NECR had the following nonlinear relationships with the body weight: SF=0.15 ṡ body weight0.3 and NECR = 421.36 (body weight)-0.84. The equation derived for FTS was 0.01ṡ body weight + 0.2, which means that, for example, a 120-kg person should be scanned 1.8 times longer than a 70 kg person, or the scan time for a 40-kg person can be reduced by 30%. Conclusion: the equation of the relative time demand derived in this study will be useful for maintaining consistent PET image quality in clinics.

Telemedicine + OCT: toward design of optimized algorithms for high-quality compressed images

NASA Astrophysics Data System (ADS)

Mousavi, Mahta; Lurie, Kristen; Land, Julian; Javidi, Tara; Ellerbee, Audrey K.

2014-03-01

Telemedicine is an emerging technology that aims to provide clinical healthcare at a distance. Among its goals, the transfer of diagnostic images over telecommunication channels has been quite appealing to the medical community. When viewed as an adjunct to biomedical device hardware, one highly important consideration aside from the transfer rate and speed is the accuracy of the reconstructed image at the receiver end. Although optical coherence tomography (OCT) is an established imaging technique that is ripe for telemedicine, the effects of OCT data compression, which may be necessary on certain telemedicine platforms, have not received much attention in the literature. We investigate the performance and efficiency of several lossless and lossy compression techniques for OCT data and characterize their effectiveness with respect to achievable compression ratio, compression rate and preservation of image quality. We examine the effects of compression in the interferogram vs. A-scan domain as assessed with various objective and subjective metrics.

How much image noise can be added in cardiac x-ray imaging without loss in perceived image quality?

NASA Astrophysics Data System (ADS)

Gislason-Lee, Amber J.; Kumcu, Asli; Kengyelics, Stephen M.; Rhodes, Laura A.; Davies, Andrew G.

2015-03-01

Dynamic X-ray imaging systems are used for interventional cardiac procedures to treat coronary heart disease. X-ray settings are controlled automatically by specially-designed X-ray dose control mechanisms whose role is to ensure an adequate level of image quality is maintained with an acceptable radiation dose to the patient. Current commonplace dose control designs quantify image quality by performing a simple technical measurement directly from the image. However, the utility of cardiac X-ray images is in their interpretation by a cardiologist during an interventional procedure, rather than in a technical measurement. With the long term goal of devising a clinically-relevant image quality metric for an intelligent dose control system, we aim to investigate the relationship of image noise with clinical professionals' perception of dynamic image sequences. Computer-generated noise was added, in incremental amounts, to angiograms of five different patients selected to represent the range of adult cardiac patient sizes. A two alternative forced choice staircase experiment was used to determine the amount of noise which can be added to a patient image sequences without changing image quality as perceived by clinical professionals. Twenty-five viewing sessions (five for each patient) were completed by thirteen observers. Results demonstrated scope to increase the noise of cardiac X-ray images by up to 21% +/- 8% before it is noticeable by clinical professionals. This indicates a potential for 21% radiation dose reduction since X-ray image noise and radiation dose are directly related; this would be beneficial to both patients and personnel.

Imaging quality analysis of multi-channel scanning radiometer

NASA Astrophysics Data System (ADS)

Fan, Hong; Xu, Wujun; Wang, Chengliang

2008-03-01

Multi-channel scanning radiometer, on boarding FY-2 geostationary meteorological satellite, plays a key role in remote sensing because of its wide field of view and continuous multi-spectral images acquirements. It is significant to evaluate image quality after performance parameters of the imaging system are validated. Several methods of evaluating imaging quality are discussed. Of these methods, the most fundamental is the MTF. The MTF of photoelectric scanning remote instrument, in the scanning direction, is the multiplication of optics transfer function (OTF), detector transfer function (DTF) and electronics transfer function (ETF). For image motion compensation, moving speed of scanning mirror should be considered. The optical MTF measurement is performed in both the EAST/WEST and NORTH/SOUTH direction, whose values are used for alignment purposes and are used to determine the general health of the instrument during integration and testing. Imaging systems cannot perfectly reproduce what they see and end up "blurring" the image. Many parts of the imaging system can cause blurring. Among these are the optical elements, the sampling of the detector itself, post-processing, or the earth's atmosphere for systems that image through it. Through theory calculation and actual measurement, it is proved that DTF and ETF are the main factors of system MTF and the imaging quality can satisfy the requirement of instrument design.

High-volume image quality assessment systems: tuning performance with an interactive data visualization tool

NASA Astrophysics Data System (ADS)

Bresnahan, Patricia A.; Pukinskis, Madeleine; Wiggins, Michael

1999-03-01

Image quality assessment systems differ greatly with respect to the number and types of mags they need to evaluate, and their overall architectures. Managers of these systems, however, all need to be able to tune and evaluate system performance, requirements often overlooked or under-designed during project planning. Performance tuning tools allow users to define acceptable quality standards for image features and attributes by adjusting parameter settings. Performance analysis tools allow users to evaluate and/or predict how well a system performs in a given parameter state. While image assessment algorithms are becoming quite sophisticated, duplicating or surpassing the human decision making process in their speed and reliability, they often require a greater investment in 'training' or fine tuning of parameters in order to achieve optimum performance. This process may involve the analysis of hundreds or thousands of images, generating a large database of files and statistics that can be difficult to sort through and interpret. Compounding the difficulty is the fact that personnel charged with tuning and maintaining the production system may not have the statistical or analytical background required for the task. Meanwhile, hardware innovations have greatly increased the volume of images that can be handled in a given time frame, magnifying the consequences of running a production site with an inadequately tuned system. In this paper, some general requirements for a performance evaluation and tuning data visualization system are discussed. A custom engineered solution to the tuning and evaluation problem is then presented, developed within the context of a high volume image quality assessment, data entry, OCR, and image archival system. A key factor influencing the design of the system was the context-dependent definition of image quality, as perceived by a human interpreter. This led to the development of a five-level, hierarchical approach to image quality

Review of spectral imaging technology in biomedical engineering: achievements and challenges.

PubMed

Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

2013-10-01

Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

Comprehensive model for predicting perceptual image quality of smart mobile devices.

PubMed

Gong, Rui; Xu, Haisong; Luo, M R; Li, Haifeng

2015-01-01

An image quality model for smart mobile devices was proposed based on visual assessments of several image quality attributes. A series of psychophysical experiments were carried out on two kinds of smart mobile devices, i.e., smart phones and tablet computers, in which naturalness, colorfulness, brightness, contrast, sharpness, clearness, and overall image quality were visually evaluated under three lighting environments via categorical judgment method for various application types of test images. On the basis of Pearson correlation coefficients and factor analysis, the overall image quality could first be predicted by its two constituent attributes with multiple linear regression functions for different types of images, respectively, and then the mathematical expressions were built to link the constituent image quality attributes with the physical parameters of smart mobile devices and image appearance factors. The procedure and algorithms were applicable to various smart mobile devices, different lighting conditions, and multiple types of images, and performance was verified by the visual data.

Scientific Achievements of Global ENA Imaging and Future Outlook

NASA Astrophysics Data System (ADS)

Brandt, P. C.; Stephens, G. K.; Hsieh, S. Y. W.; Demajistre, R.; Gkioulidou, M.

2017-12-01

Energetic Neutral Atom (ENA) imaging is the only technique that can capture the instantaneous global state of energetic ion distributions in planetary magnetospheres and from the heliosheath. In particular at Earth, ENA imaging has been used to diagnose the morphology and dynamics of the ring current and plasma sheet down to several minutes time resolution and is therefore a critical tool to validate global ring current physics models. However, this requires a detailed understanding for how ENAs are produced from the ring current and inversion techniques that are thoroughly validated against in-situ measurements. To date, several missions have carried out planetary and heliospheric ENA imaging including Cassini, JUICE, IBEX of the heliosphere, and POLAR, Astrid-1, Double Star, TWINS and IMAGE of the terrestrial magnetosphere. Because of their path-finding successes, a future global-imaging mission concept, MEDICI, has been recommended in the Heliophysics Decadal Survey. Its core mission consists of two satellites in one circular, near-polar orbit beyond the radiation belts at around 8 RE, with ENA, EUV and FUV cameras. This recommendation has driven the definition of smaller mission concepts that address specific science aspects of the MEDICI concept. In this presentation, we review the past scientific achievements of ENA imaging with a focus on the terrestrial magnetosphere from primarily the NASA IMAGE and the TWINS missions. The highlighted achievements include the storm, sub-storm and quiet-time morphology, dynamics and pitch-angle distributions of the ring current, global differential acceleration of protons versus O+ ions, the structure of the global electrical current systems associated with the plasma pressure of protons and O+ ions up to around 200 keV, and the relation between ring current and plasmasphere. We discuss the need for future global observations of the ring current, plasma sheet and magnetosheath ion distributions based and derive their

Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.

PubMed

Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel

2017-07-28

New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.

Applying image quality in cell phone cameras: lens distortion

NASA Astrophysics Data System (ADS)

Baxter, Donald; Goma, Sergio R.; Aleksic, Milivoje

2009-01-01

This paper describes the framework used in one of the pilot studies run under the I3A CPIQ initiative to quantify overall image quality in cell-phone cameras. The framework is based on a multivariate formalism which tries to predict overall image quality from individual image quality attributes and was validated in a CPIQ pilot program. The pilot study focuses on image quality distortions introduced in the optical path of a cell-phone camera, which may or may not be corrected in the image processing path. The assumption is that the captured image used is JPEG compressed and the cellphone camera is set to 'auto' mode. As the used framework requires that the individual attributes to be relatively perceptually orthogonal, in the pilot study, the attributes used are lens geometric distortion (LGD) and lateral chromatic aberrations (LCA). The goal of this paper is to present the framework of this pilot project starting with the definition of the individual attributes, up to their quantification in JNDs of quality, a requirement of the multivariate formalism, therefore both objective and subjective evaluations were used. A major distinction in the objective part from the 'DSC imaging world' is that the LCA/LGD distortions found in cell-phone cameras, rarely exhibit radial behavior, therefore a radial mapping/modeling cannot be used in this case.

Objective Assessment of Image Quality VI: Imaging in Radiation Therapy

PubMed Central

Barrett, Harrison H.; Kupinski, Matthew A.; Müeller, Stefan; Halpern, Howard J.; Morris, John C.; Dwyer, Roisin

2015-01-01

Earlier work on Objective Assessment of Image Quality (OAIQ) focused largely on estimation or classification tasks in which the desired outcome of imaging is accurate diagnosis. This paper develops a general framework for assessing imaging quality on the basis of therapeutic outcomes rather than diagnostic performance. By analogy to Receiver Operating Characteristic (ROC) curves and their variants as used in diagnostic OAIQ, the method proposed here utilizes the Therapy Operating Characteristic or TOC curves, which are plots of the probability of tumor control vs. the probability of normal-tissue complications as the overall dose level of a radiotherapy treatment is varied. The proposed figure of merit is the area under the TOC curve, denoted AUTOC. This paper reviews an earlier exposition of the theory of TOC and AUTOC, which was specific to the assessment of image-segmentation algorithms, and extends it to other applications of imaging in external-beam radiation treatment as well as in treatment with internal radioactive sources. For each application, a methodology for computing the TOC is presented. A key difference between ROC and TOC is that the latter can be defined for a single patient rather than a population of patients. PMID:24200954

Landsat image data quality studies

NASA Technical Reports Server (NTRS)

Schueler, C. F.; Salomonson, V. V.

1985-01-01

Preliminary results of the Landsat-4 Image Data Quality Analysis (LIDQA) program to characterize the data obtained using the Thematic Mapper (TM) instrument on board the Landsat-4 and Landsat-5 satellites are reported. TM design specifications were compared to the obtained data with respect to four criteria, including spatial resolution; geometric fidelity; information content; and image relativity to Multispectral Scanner (MSS) data. The overall performance of the TM was rated excellent despite minor instabilities and radiometric anomalies in the data. Spatial performance of the TM exceeded design specifications in terms of both image sharpness and geometric accuracy, and the image utility of the TM data was at least twice as high as MSS data. The separability of alfalfa and sugar beet fields in a TM image is demonstrated.

Human visual system consistent quality assessment for remote sensing image fusion

NASA Astrophysics Data System (ADS)

Liu, Jun; Huang, Junyi; Liu, Shuguang; Li, Huali; Zhou, Qiming; Liu, Junchen

2015-07-01

Quality assessment for image fusion is essential for remote sensing application. Generally used indices require a high spatial resolution multispectral (MS) image for reference, which is not always readily available. Meanwhile, the fusion quality assessments using these indices may not be consistent with the Human Visual System (HVS). As an attempt to overcome this requirement and inconsistency, this paper proposes an HVS-consistent image fusion quality assessment index at the highest resolution without a reference MS image using Gaussian Scale Space (GSS) technology that could simulate the HVS. The spatial details and spectral information of original and fused images are first separated in GSS, and the qualities are evaluated using the proposed spatial and spectral quality index respectively. The overall quality is determined without a reference MS image by a combination of the proposed two indices. Experimental results on various remote sensing images indicate that the proposed index is more consistent with HVS evaluation compared with other widely used indices that may or may not require reference images.

Digital radiography: optimization of image quality and dose using multi-frequency software.

PubMed

Precht, H; Gerke, O; Rosendahl, K; Tingberg, A; Waaler, D

2012-09-01

New developments in processing of digital radiographs (DR), including multi-frequency processing (MFP), allow optimization of image quality and radiation dose. This is particularly promising in children as they are believed to be more sensitive to ionizing radiation than adults. To examine whether the use of MFP software reduces the radiation dose without compromising quality at DR of the femur in 5-year-old-equivalent anthropomorphic and technical phantoms. A total of 110 images of an anthropomorphic phantom were imaged on a DR system (Canon DR with CXDI-50 C detector and MLT[S] software) and analyzed by three pediatric radiologists using Visual Grading Analysis. In addition, 3,500 images taken of a technical contrast-detail phantom (CDRAD 2.0) provide an objective image-quality assessment. Optimal image-quality was maintained at a dose reduction of 61% with MLT(S) optimized images. Even for images of diagnostic quality, MLT(S) provided a dose reduction of 88% as compared to the reference image. Software impact on image quality was found significant for dose (mAs), dynamic range dark region and frequency band. By optimizing image processing parameters, a significant dose reduction is possible without significant loss of image quality.

Enhancement of digital radiography image quality using a convolutional neural network.

PubMed

Sun, Yuewen; Li, Litao; Cong, Peng; Wang, Zhentao; Guo, Xiaojing

2017-01-01

Digital radiography system is widely used for noninvasive security check and medical imaging examination. However, the system has a limitation of lower image quality in spatial resolution and signal to noise ratio. In this study, we explored whether the image quality acquired by the digital radiography system can be improved with a modified convolutional neural network to generate high-resolution images with reduced noise from the original low-quality images. The experiment evaluated on a test dataset, which contains 5 X-ray images, showed that the proposed method outperformed the traditional methods (i.e., bicubic interpolation and 3D block-matching approach) as measured by peak signal to noise ratio (PSNR) about 1.3 dB while kept highly efficient processing time within one second. Experimental results demonstrated that a residual to residual (RTR) convolutional neural network remarkably improved the image quality of object structural details by increasing the image resolution and reducing image noise. Thus, this study indicated that applying this RTR convolutional neural network system was useful to improve image quality acquired by the digital radiography system.

High-quality JPEG compression history detection for fake uncompressed images

NASA Astrophysics Data System (ADS)

Zhang, Rong; Wang, Rang-Ding; Guo, Li-Jun; Jiang, Bao-Chuan

2017-05-01

Authenticity is one of the most important evaluation factors of images for photography competitions or journalism. Unusual compression history of an image often implies the illicit intent of its author. Our work aims at distinguishing real uncompressed images from fake uncompressed images that are saved in uncompressed formats but have been previously compressed. To detect the potential image JPEG compression, we analyze the JPEG compression artifacts based on the tetrolet covering, which corresponds to the local image geometrical structure. Since the compression can alter the structure information, the tetrolet covering indexes may be changed if a compression is performed on the test image. Such changes can provide valuable clues about the image compression history. To be specific, the test image is first compressed with different quality factors to generate a set of temporary images. Then, the test image is compared with each temporary image block-by-block to investigate whether the tetrolet covering index of each 4×4 block is different between them. The percentages of the changed tetrolet covering indexes corresponding to the quality factors (from low to high) are computed and used to form the p-curve, the local minimum of which may indicate the potential compression. Our experimental results demonstrate the advantage of our method to detect JPEG compressions of high quality, even the highest quality factors such as 98, 99, or 100 of the standard JPEG compression, from uncompressed-format images. At the same time, our detection algorithm can accurately identify the corresponding compression quality factor.

Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index.

PubMed

Xue, Wufeng; Zhang, Lei; Mou, Xuanqin; Bovik, Alan C

2014-02-01

It is an important task to faithfully evaluate the perceptual quality of output images in many applications, such as image compression, image restoration, and multimedia streaming. A good image quality assessment (IQA) model should not only deliver high quality prediction accuracy, but also be computationally efficient. The efficiency of IQA metrics is becoming particularly important due to the increasing proliferation of high-volume visual data in high-speed networks. We present a new effective and efficient IQA model, called gradient magnitude similarity deviation (GMSD). The image gradients are sensitive to image distortions, while different local structures in a distorted image suffer different degrees of degradations. This motivates us to explore the use of global variation of gradient based local quality map for overall image quality prediction. We find that the pixel-wise gradient magnitude similarity (GMS) between the reference and distorted images combined with a novel pooling strategy-the standard deviation of the GMS map-can predict accurately perceptual image quality. The resulting GMSD algorithm is much faster than most state-of-the-art IQA methods, and delivers highly competitive prediction accuracy. MATLAB source code of GMSD can be downloaded at http://www4.comp.polyu.edu.hk/~cslzhang/IQA/GMSD/GMSD.htm.

Blind CT image quality assessment via deep learning strategy: initial study

NASA Astrophysics Data System (ADS)

Li, Sui; He, Ji; Wang, Yongbo; Liao, Yuting; Zeng, Dong; Bian, Zhaoying; Ma, Jianhua

2018-03-01

Computed Tomography (CT) is one of the most important medical imaging modality. CT images can be used to assist in the detection and diagnosis of lesions and to facilitate follow-up treatment. However, CT images are vulnerable to noise. Actually, there are two major source intrinsically causing the CT data noise, i.e., the X-ray photo statistics and the electronic noise background. Therefore, it is necessary to doing image quality assessment (IQA) in CT imaging before diagnosis and treatment. Most of existing CT images IQA methods are based on human observer study. However, these methods are impractical in clinical for their complex and time-consuming. In this paper, we presented a blind CT image quality assessment via deep learning strategy. A database of 1500 CT images is constructed, containing 300 high-quality images and 1200 corresponding noisy images. Specifically, the high-quality images were used to simulate the corresponding noisy images at four different doses. Then, the images are scored by the experienced radiologists by the following attributes: image noise, artifacts, edge and structure, overall image quality, and tumor size and boundary estimation with five-point scale. We trained a network for learning the non-liner map from CT images to subjective evaluation scores. Then, we load the pre-trained model to yield predicted score from the test image. To demonstrate the performance of the deep learning network in IQA, correlation coefficients: Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are utilized. And the experimental result demonstrate that the presented deep learning based IQA strategy can be used in the CT image quality assessment.

Integrating prior information into microwave tomography Part 1: Impact of detail on image quality.

PubMed

Kurrant, Douglas; Baran, Anastasia; LoVetri, Joe; Fear, Elise

2017-12-01

The authors investigate the impact that incremental increases in the level of detail of patient-specific prior information have on image quality and the convergence behavior of an inversion algorithm in the context of near-field microwave breast imaging. A methodology is presented that uses image quality measures to characterize the ability of the algorithm to reconstruct both internal structures and lesions embedded in fibroglandular tissue. The approach permits key aspects that impact the quality of reconstruction of these structures to be identified and quantified. This provides insight into opportunities to improve image reconstruction performance. Patient-specific information is acquired using radar-based methods that form a regional map of the breast. This map is then incorporated into a microwave tomography algorithm. Previous investigations have demonstrated the effectiveness of this approach to improve image quality when applied to data generated with two-dimensional (2D) numerical models. The present study extends this work by generating prior information that is customized to vary the degree of structural detail to facilitate the investigation of the role of prior information in image formation. Numerical 2D breast models constructed from magnetic resonance (MR) scans, and reconstructions formed with a three-dimensional (3D) numerical breast model are used to assess if trends observed for the 2D results can be extended to 3D scenarios. For the blind reconstruction scenario (i.e., no prior information), the breast surface is not accurately identified and internal structures are not clearly resolved. A substantial improvement in image quality is achieved by incorporating the skin surface map and constraining the imaging domain to the breast. Internal features within the breast appear in the reconstructed image. However, it is challenging to discriminate between adipose and glandular regions and there are inaccuracies in both the structural properties of

A database for spectral image quality

NASA Astrophysics Data System (ADS)

Le Moan, Steven; George, Sony; Pedersen, Marius; Blahová, Jana; Hardeberg, Jon Yngve

2015-01-01

We introduce a new image database dedicated to multi-/hyperspectral image quality assessment. A total of nine scenes representing pseudo-at surfaces of different materials (textile, wood, skin. . . ) were captured by means of a 160 band hyperspectral system with a spectral range between 410 and 1000nm. Five spectral distortions were designed, applied to the spectral images and subsequently compared in a psychometric experiment, in order to provide a basis for applications such as the evaluation of spectral image difference measures. The database can be downloaded freely from http://www.colourlab.no/cid.

Survey of the prevalence and methodology of quality assurance for B-mode ultrasound image quality among veterinary sonographers.

PubMed

Hoscheit, Larry P; Heng, Hock Gan; Lim, Chee Kin; Weng, Hsin-Yi

2018-05-01

Image quality in B-mode ultrasound is important as it reflects the diagnostic accuracy and diagnostic information provided during clinical scanning. Quality assurance programs for B-mode ultrasound systems/components are comprised of initial quality acceptance testing and subsequent regularly scheduled quality control testing. The importance of quality assurance programs for B-mode ultrasound image quality using ultrasound phantoms is well documented in the human medical and medical physics literature. The purpose of this prospective, cross-sectional, survey study was to determine the prevalence and methodology of quality acceptance testing and quality control testing of image quality for ultrasound system/components among veterinary sonographers. An online electronic survey was sent to 1497 members of veterinary imaging organizations: the American College of Veterinary Radiology, the Veterinary Ultrasound Society, and the European Association of Veterinary Diagnostic Imaging, and a total of 167 responses were received. The results showed that the percentages of veterinary sonographers performing quality acceptance testing and quality control testing are 42% (64/151; 95% confidence interval 34-52%) and 26% (40/156: 95% confidence interval 19-33%) respectively. Of the respondents who claimed to have quality acceptance testing or quality control testing of image quality in place for their ultrasound system/components, 0% have performed quality acceptance testing or quality control testing correctly (quality acceptance testing 95% confidence interval: 0-6%, quality control testing 95% confidence interval: 0-11%). Further education and guidelines are recommended for veterinary sonographers in the area of quality acceptance testing and quality control testing for B-mode ultrasound equipment/components. © 2018 American College of Veterinary Radiology.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose.

PubMed

Aurumskjöld, Marie-Louise; Söderberg, Marcus; Stålhammar, Fredrik; von Steyern, Kristina Vult; Tingberg, Anders; Ydström, Kristina

2018-06-01

Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose 4 ), and images from the low-dose examinations were reconstructed with both iDose 4 and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose 4 and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose 4 images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60-0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose 4 method for evaluating pediatric abdominal CT, even with a 32% dose reduction.

Effects of task and image properties on visual-attention deployment in image-quality assessment

NASA Astrophysics Data System (ADS)

Alers, Hani; Redi, Judith; Liu, Hantao; Heynderickx, Ingrid

2015-03-01

It is important to understand how humans view images and how their behavior is affected by changes in the properties of the viewed images and the task they are given, particularly the task of scoring the image quality (IQ). This is a complex behavior that holds great importance for the field of image-quality research. This work builds upon 4 years of research work spanning three databases studying image-viewing behavior. Using eye-tracking equipment, it was possible to collect information on human viewing behavior of different kinds of stimuli and under different experimental settings. This work performs a cross-analysis on the results from all these databases using state-of-the-art similarity measures. The results strongly show that asking the viewers to score the IQ significantly changes their viewing behavior. Also muting the color saturation seems to affect the saliency of the images. However, a change in IQ was not consistently found to modify visual attention deployment, neither under free looking nor during scoring. These results are helpful in gaining a better understanding of image viewing behavior under different conditions. They also have important implications on work that collects subjective image-quality scores from human observers.

Objective Quality Assessment for Color-to-Gray Image Conversion.

PubMed

Ma, Kede; Zhao, Tiesong; Zeng, Kai; Wang, Zhou

2015-12-01

Color-to-gray (C2G) image conversion is the process of transforming a color image into a grayscale one. Despite its wide usage in real-world applications, little work has been dedicated to compare the performance of C2G conversion algorithms. Subjective evaluation is reliable but is also inconvenient and time consuming. Here, we make one of the first attempts to develop an objective quality model that automatically predicts the perceived quality of C2G converted images. Inspired by the philosophy of the structural similarity index, we propose a C2G structural similarity (C2G-SSIM) index, which evaluates the luminance, contrast, and structure similarities between the reference color image and the C2G converted image. The three components are then combined depending on image type to yield an overall quality measure. Experimental results show that the proposed C2G-SSIM index has close agreement with subjective rankings and significantly outperforms existing objective quality metrics for C2G conversion. To explore the potentials of C2G-SSIM, we further demonstrate its use in two applications: 1) automatic parameter tuning for C2G conversion algorithms and 2) adaptive fusion of C2G converted images.

MO-DE-209-03: Assessing Image Quality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, W.

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBTmore » shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research

The effect of image quality, repeated study, and assessment method on anatomy learning.

PubMed

Fenesi, Barbara; Mackinnon, Chelsea; Cheng, Lucia; Kim, Joseph A; Wainman, Bruce C

2017-06-01

The use of two-dimensional (2D) images is consistently used to prepare anatomy students for handling real specimen. This study examined whether the quality of 2D images is a critical component in anatomy learning. The visual clarity and consistency of 2D anatomical images was systematically manipulated to produce low-quality and high-quality images of the human hand and human eye. On day 0, participants learned about each anatomical specimen from paper booklets using either low-quality or high-quality images, and then completed a comprehension test using either 2D images or three-dimensional (3D) cadaveric specimens. On day 1, participants relearned each booklet, and on day 2 participants completed a final comprehension test using either 2D images or 3D cadaveric specimens. The effect of image quality on learning varied according to anatomical content, with high-quality images having a greater effect on improving learning of hand anatomy than eye anatomy (high-quality vs. low-quality for hand anatomy P = 0.018; high-quality vs. low-quality for eye anatomy P = 0.247). Also, the benefit of high-quality images on hand anatomy learning was restricted to performance on short-answer (SA) questions immediately after learning (high-quality vs. low-quality on SA questions P = 0.018), but did not apply to performance on multiple-choice (MC) questions (high-quality vs. low-quality on MC questions P = 0.109) or after participants had an additional learning opportunity (24 hours later) with anatomy content (high vs. low on SA questions P = 0.643). This study underscores the limited impact of image quality on anatomy learning, and questions whether investment in enhancing image quality of learning aids significantly promotes knowledge development. Anat Sci Educ 10: 249-261. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Image Quality Assessment of JPEG Compressed Mars Science Laboratory Mastcam Images using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Kerner, H. R.; Bell, J. F., III; Ben Amor, H.

2017-12-01

The Mastcam color imaging system on the Mars Science Laboratory Curiosity rover acquires images within Gale crater for a variety of geologic and atmospheric studies. Images are often JPEG compressed before being downlinked to Earth. While critical for transmitting images on a low-bandwidth connection, this compression can result in image artifacts most noticeable as anomalous brightness or color changes within or near JPEG compression block boundaries. In images with significant high-frequency detail (e.g., in regions showing fine layering or lamination in sedimentary rocks), the image might need to be re-transmitted losslessly to enable accurate scientific interpretation of the data. The process of identifying which images have been adversely affected by compression artifacts is performed manually by the Mastcam science team, costing significant expert human time. To streamline the tedious process of identifying which images might need to be re-transmitted, we present an input-efficient neural network solution for predicting the perceived quality of a compressed Mastcam image. Most neural network solutions require large amounts of hand-labeled training data for the model to learn the target mapping between input (e.g. distorted images) and output (e.g. quality assessment). We propose an automatic labeling method using joint entropy between a compressed and uncompressed image to avoid the need for domain experts to label thousands of training examples by hand. We use automatically labeled data to train a convolutional neural network to estimate the probability that a Mastcam user would find the quality of a given compressed image acceptable for science analysis. We tested our model on a variety of Mastcam images and found that the proposed method correlates well with image quality perception by science team members. When assisted by our proposed method, we estimate that a Mastcam investigator could reduce the time spent reviewing images by a minimum of 70%.

Multiple Image Arrangement for Subjective Quality Assessment

NASA Astrophysics Data System (ADS)

Wang, Yan; Zhai, Guangtao

2017-12-01

Subjective quality assessment serves as the foundation for almost all visual quality related researches. Size of the image quality databases has expanded from dozens to thousands in the last decades. Since each subjective rating therein has to be averaged over quite a few participants, the ever-increasing overall size of those databases calls for an evolution of existing subjective test methods. Traditional single/double stimulus based approaches are being replaced by multiple image tests, where several distorted versions of the original one are displayed and rated at once. And this naturally brings upon the question of how to arrange those multiple images on screen during the test. In this paper, we answer this question by performing subjective viewing test with eye tracker for different types arrangements. Our research indicates that isometric arrangement imposes less duress on participants and has more uniform distribution of eye fixations and movements and therefore is expected to generate more reliable subjective ratings.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Raising Quality and Achievement. A College Guide to Benchmarking.

ERIC Educational Resources Information Center

Owen, Jane

This booklet introduces the principles and practices of benchmarking as a way of raising quality and achievement at further education colleges in Britain. Section 1 defines the concept of benchmarking. Section 2 explains what benchmarking is not and the steps that should be taken before benchmarking is initiated. The following aspects and…

Effect of image quality on calcification detection in digital mammography

PubMed Central

Warren, Lucy M.; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind M.; Wallis, Matthew G.; Chakraborty, Dev P.; Dance, David R.; Bosmans, Hilde; Young, Kenneth C.

2012-01-01

Purpose: This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. Methods: One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. Results: There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC

Effect of image quality on calcification detection in digital mammography.

PubMed

Warren, Lucy M; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind M; Wallis, Matthew G; Chakraborty, Dev P; Dance, David R; Bosmans, Hilde; Young, Kenneth C

2012-06-01

This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from

Image quality of conventional images of dual-layer SPECTRAL CT: A phantom study.

PubMed

van Ommen, Fasco; Bennink, Edwin; Vlassenbroek, Alain; Dankbaar, Jan Willem; Schilham, Arnold M R; Viergever, Max A; de Jong, Hugo W A M

2018-05-10

Spectral CT using a dual layer detector offers the possibility of retrospectively introducing spectral information to conventional CT images. In theory, the dual-layer technology should not come with a dose or image quality penalty for conventional images. In this study, we evaluate the influence of a dual-layer detector (IQon Spectral CT, Philips Healthcare) on the image quality of conventional CT images, by comparing these images with those of a conventional but otherwise technically comparable single-layer CT scanner (Brilliance iCT, Philips Healthcare), by means of phantom experiments. For both CT scanners, conventional CT images were acquired using four adult scanning protocols: (a) body helical, (b) body axial, (c) head helical, and (d) head axial. A CATPHAN 600 phantom was scanned to conduct an assessment of image quality metrics at equivalent (CTDI) dose levels. Noise was characterized by means of noise power spectra (NPS) and standard deviation (SD) of a uniform region, and spatial resolution was evaluated with modulation transfer functions (MTF) of a tungsten wire. In addition, contrast-to-noise ratio (CNR), image uniformity, CT number linearity, slice thickness, slice spacing, and spatial linearity were measured and evaluated. Additional measurements of CNR, resolution and noise were performed in two larger phantoms. The resolution levels at 50%, 10%, and 5% MTF of the iCT and IQon showed small, but significant differences up to 0.25 lp/cm for body scans, and up to 0.2 lp/cm for head scans in favor of the IQon. The iCT and IQon showed perfect CT linearity for body scans, but for head scans both scanners showed an underestimation of the CT numbers of materials with a high opacity. Slice thickness was slightly overestimated for both scanners. Slice spacing was comparable and reconstructed correctly. In addition, spatial linearity was excellent for both scanners, with a maximum error of 0.11 mm. CNR was higher on the IQon compared to the iCT for both normal

Fuzzy intelligent quality monitoring model for X-ray image processing.

PubMed

Khalatbari, Azadeh; Jenab, Kouroush

2009-01-01

Today's imaging diagnosis needs to adapt modern techniques of quality engineering to maintain and improve its accuracy and reliability in health care system. One of the main factors that influences diagnostic accuracy of plain film X-ray on detecting pathology is the level of film exposure. If the level of film exposure is not adequate, a normal body structure may be interpretated as pathology and vice versa. This not only influences the patient management but also has an impact on health care cost and patient's quality of life. Therefore, providing an accurate and high quality image is the first step toward an excellent patient management in any health care system. In this paper, we study these techniques and also present a fuzzy intelligent quality monitoring model, which can be used to keep variables from degrading the image quality. The variables derived from chemical activity, cleaning procedures, maintenance, and monitoring may not be sensed, measured, or calculated precisely due to uncertain situations. Therefore, the gamma-level fuzzy Bayesian model for quality monitoring of an image processing is proposed. In order to apply the Bayesian concept, the fuzzy quality characteristics are assumed as fuzzy random variables. Using the fuzzy quality characteristics, the newly developed model calculates the degradation risk for image processing. A numerical example is also presented to demonstrate the application of the model.

Backward Registration Based Aspect Ratio Similarity (ARS) for Image Retargeting Quality Assessment.

PubMed

Zhang, Yabin; Fang, Yuming; Lin, Weisi; Zhang, Xinfeng; Li, Leida

2016-06-28

During the past few years, there have been various kinds of content-aware image retargeting operators proposed for image resizing. However, the lack of effective objective retargeting quality assessment metrics limits the further development of image retargeting techniques. Different from traditional Image Quality Assessment (IQA) metrics, the quality degradation during image retargeting is caused by artificial retargeting modifications, and the difficulty for Image Retargeting Quality Assessment (IRQA) lies in the alternation of the image resolution and content, which makes it impossible to directly evaluate the quality degradation like traditional IQA. In this paper, we interpret the image retargeting in a unified framework of resampling grid generation and forward resampling. We show that the geometric change estimation is an efficient way to clarify the relationship between the images. We formulate the geometric change estimation as a Backward Registration problem with Markov Random Field (MRF) and provide an effective solution. The geometric change aims to provide the evidence about how the original image is resized into the target image. Under the guidance of the geometric change, we develop a novel Aspect Ratio Similarity metric (ARS) to evaluate the visual quality of retargeted images by exploiting the local block changes with a visual importance pooling strategy. Experimental results on the publicly available MIT RetargetMe and CUHK datasets demonstrate that the proposed ARS can predict more accurate visual quality of retargeted images compared with state-of-the-art IRQA metrics.

Image quality testing of assembled IR camera modules

NASA Astrophysics Data System (ADS)

Winters, Daniel; Erichsen, Patrik

2013-10-01

Infrared (IR) camera modules for the LWIR (8-12_m) that combine IR imaging optics with microbolometer focal plane array (FPA) sensors with readout electronics are becoming more and more a mass market product. At the same time, steady improvements in sensor resolution in the higher priced markets raise the requirement for imaging performance of objectives and the proper alignment between objective and FPA. This puts pressure on camera manufacturers and system integrators to assess the image quality of finished camera modules in a cost-efficient and automated way for quality control or during end-of-line testing. In this paper we present recent development work done in the field of image quality testing of IR camera modules. This technology provides a wealth of additional information in contrast to the more traditional test methods like minimum resolvable temperature difference (MRTD) which give only a subjective overall test result. Parameters that can be measured are image quality via the modulation transfer function (MTF) for broadband or with various bandpass filters on- and off-axis and optical parameters like e.g. effective focal length (EFL) and distortion. If the camera module allows for refocusing the optics, additional parameters like best focus plane, image plane tilt, auto-focus quality, chief ray angle etc. can be characterized. Additionally, the homogeneity and response of the sensor with the optics can be characterized in order to calculate the appropriate tables for non-uniformity correction (NUC). The technology can also be used to control active alignment methods during mechanical assembly of optics to high resolution sensors. Other important points that are discussed are the flexibility of the technology to test IR modules with different form factors, electrical interfaces and last but not least the suitability for fully automated measurements in mass production.

Whole-body CT in polytrauma patients: The effect of arm position on abdominal image quality when using a human phantom

NASA Astrophysics Data System (ADS)

Jeon, Pil-Hyun; Kim, Hee-Joung; Lee, Chang-Lae; Kim, Dae-Hong; Lee, Won-Hyung; Jeon, Sung-Su

2012-06-01

For a considerable number of emergency computed tomography (CT) scans, patients are unable to position their arms above their head due to traumatic injuries. The arms-down position has been shown to reduce image quality with beam-hardening artifacts in the dorsal regions of the liver, spleen, and kidneys, rendering these images non-diagnostic. The purpose of this study was to evaluate the effect of arm position on the image quality in patients undergoing whole-body CT. We acquired CT scans with various acquisition parameters at voltages of 80, 120, and 140 kVp and an increasing tube current from 200 to 400 mAs in 50 mAs increments. The image noise and the contrast assessment were considered for quantitative analyses of the CT images. The image noise (IN), the contrast-to-noise ratio (CNR), the signal-to-noise ratio (SNR), and the coefficient of variation (COV) were evaluated. Quantitative analyses of the experiments were performed with CT scans representative of five different arm positions. Results of the CT scans acquired at 120 kVp and 250 mAs showed high image quality in patients with both arms raised above the head (SNR: 12.4, CNR: 10.9, and COV: 8.1) and both arms flexed at the elbows on the chest (SNR: 11.5, CNR: 10.2, and COV: 8.8) while the image quality significantly decreased with both arms in the down position (SNR: 9.1, CNR: 7.6, and COV: 11). Both arms raised, one arm raised, and both arms flexed improved the image quality compared to arms in the down position by reducing beam-hardening and streak artifacts caused by the arms being at the side of body. This study provides optimal methods for achieving higher image quality and lower noise in abdominal CT for trauma patients.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images.

PubMed

Mraity, Hussien A A B; England, Andrew; Cassidy, Simon; Eachus, Peter; Dominguez, Alejandro; Hogg, Peter

2016-01-01

The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images

PubMed Central

England, Andrew; Cassidy, Simon; Eachus, Peter; Dominguez, Alejandro; Hogg, Peter

2016-01-01

Objective: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. Methods: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. Results: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). Conclusion: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. Advances in knowledge: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality. PMID:26943836

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system.

PubMed

Moore, C S; Wood, T J; Beavis, A W; Saunderson, J R

2013-07-01

The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system. The results of a previously published study, in which four experienced image evaluators graded computer-simulated postero-anterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson's correlation coefficient. Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R=0.87, p<0.033) and eDE (R=0.77, p<0.008) were observed. Medical physics experts may use the physical image quality metrics described here in quality assurance programmes and optimisation studies with a degree of confidence that they reflect the clinical image quality in chest CR images acquired without an antiscatter grid. A statistically significant correlation has been found between the clinical and physical image quality in CR chest imaging. The results support the value of using CNR and eDE in the evaluation of quality in clinical thorax radiography.

Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system

PubMed Central

Wood, T J; Beavis, A W; Saunderson, J R

2013-01-01

Objective: The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system. Methods: The results of a previously published study, in which four experienced image evaluators graded computer-simulated postero-anterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson’s correlation coefficient. Results: Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R=0.87, p<0.033) and eDE (R=0.77, p<0.008) were observed. Conclusion: Medical physics experts may use the physical image quality metrics described here in quality assurance programmes and optimisation studies with a degree of confidence that they reflect the clinical image quality in chest CR images acquired without an antiscatter grid. Advances in knowledge: A statistically significant correlation has been found between the clinical and physical image quality in CR chest imaging. The results support the value of using CNR and eDE in the evaluation of quality in clinical thorax radiography. PMID:23568362

Zoom Reconstruction Tool: Evaluation of Image Quality and Influence on the Diagnosis of Root Fracture.

PubMed

Queiroz, Polyane Mazucatto; Santaella, Gustavo Machado; Capelozza, Ana Lúcia Alvares; Rosalen, Pedro Luiz; Freitas, Deborah Queiroz; Haiter-Neto, Francisco

2018-04-01

This study evaluated the image quality and the diagnosis of root fractures when using the Zoom Reconstruction tool (J Morita, Kyoto, Japan). A utility wax phantom with a metal sample inside was used for objective evaluation, and a mandible with 27 single-rooted teeth (with and without obturation and with and without vertical or horizontal fractures) was used for diagnostic evaluation. The images were acquired in 3 protocols: protocol 1, field of view (FOV) of 4 × 4 cm and a voxel size of 0.08 mm; protocol 2, FOV of 10 × 10 cm and a voxel size of 0.2 mm; and protocol 3, Zoom Reconstruction of images from protocol 2 (FOV of 4 × 4 cm and a voxel size of 0.08 mm). The objective evaluation was achieved by measuring the image noise, and the diagnosis of fractures was performed by 3 evaluators. The area under the receiver operating characteristic curve was used to calculate accuracy, and analysis of variance compared the accuracy and image quality of the protocols. Regarding quality, protocol 1 was superior to protocol 2 (P < .0001) and Zoom Reconstruction (P < .0001). Additionally, images of protocol 2 presented less noise than the Zoom Reconstruction image (P < .0001); however, for diagnosis, Zoom Reconstruction was superior in relation to protocol 2 (P = .011) and did not differ from protocol 1 (P = .228) for the diagnosis of a vertical root fracture in filled teeth. The Zoom Reconstruction tool allows better accuracy for vertical root fracture detection in filled teeth, making it possible to obtain a higher-resolution image from a lower-resolution examination without having to expose the patient to more radiation. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Real-time computer treatment of THz passive device images with the high image quality

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2012-06-01

We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.

The mobile image quality survey game

NASA Astrophysics Data System (ADS)

Rasmussen, D. René

2012-01-01

In this paper we discuss human assessment of the quality of photographic still images, that are degraded in various manners relative to an original, for example due to compression or noise. In particular, we examine and present results from a technique where observers view images on a mobile device, perform pairwise comparisons, identify defects in the images, and interact with the display to indicate the location of the defects. The technique measures the response time and accuracy of the responses. By posing the survey in a form similar to a game, providing performance feedback to the observer, the technique attempts to increase the engagement of the observers, and to avoid exhausting observers, a factor that is often a problem for subjective surveys. The results are compared with the known physical magnitudes of the defects and with results from similar web-based surveys. The strengths and weaknesses of the technique are discussed. Possible extensions of the technique to video quality assessment are also discussed.

Perceived assessment metrics for visible and infrared color fused image quality without reference image

NASA Astrophysics Data System (ADS)

Yu, Xuelian; Chen, Qian; Gu, Guohua; Ren, Jianle; Sui, Xiubao

2015-02-01

Designing objective quality assessment of color-fused image is a very demanding and challenging task. We propose four no-reference metrics based on human visual system characteristics for objectively evaluating the quality of false color fusion image. The perceived edge metric (PEM) is defined based on visual perception model and color image gradient similarity between the fused image and the source images. The perceptual contrast metric (PCM) is established associating multi-scale contrast and varying contrast sensitivity filter (CSF) with color components. The linear combination of the standard deviation and mean value over the fused image construct the image colorfulness metric (ICM). The color comfort metric (CCM) is designed by the average saturation and the ratio of pixels with high and low saturation. The qualitative and quantitative experimental results demonstrate that the proposed metrics have a good agreement with subjective perception.

Measuring saliency in images: which experimental parameters for the assessment of image quality?

NASA Astrophysics Data System (ADS)

Fredembach, Clement; Woolfe, Geoff; Wang, Jue

2012-01-01

Predicting which areas of an image are perceptually salient or attended to has become an essential pre-requisite of many computer vision applications. Because observers are notoriously unreliable in remembering where they look a posteriori, and because asking where they look while observing the image necessarily in uences the results, ground truth about saliency and visual attention has to be obtained by gaze tracking methods. From the early work of Buswell and Yarbus to the most recent forays in computer vision there has been, perhaps unfortunately, little agreement on standardisation of eye tracking protocols for measuring visual attention. As the number of parameters involved in experimental methodology can be large, their individual in uence on the nal results is not well understood. Consequently, the performance of saliency algorithms, when assessed by correlation techniques, varies greatly across the literature. In this paper, we concern ourselves with the problem of image quality. Specically: where people look when judging images. We show that in this case, the performance gap between existing saliency prediction algorithms and experimental results is signicantly larger than otherwise reported. To understand this discrepancy, we rst devise an experimental protocol that is adapted to the task of measuring image quality. In a second step, we compare our experimental parameters with the ones of existing methods and show that a lot of the variability can directly be ascribed to these dierences in experimental methodology and choice of variables. In particular, the choice of a task, e.g., judging image quality vs. free viewing, has a great impact on measured saliency maps, suggesting that even for a mildly cognitive task, ground truth obtained by free viewing does not adapt well. Careful analysis of the prior art also reveals that systematic bias can occur depending on instrumental calibration and the choice of test images. We conclude this work by proposing a

Medical Image Processing Server applied to Quality Control of Nuclear Medicine.

NASA Astrophysics Data System (ADS)

Vergara, C.; Graffigna, J. P.; Marino, E.; Omati, S.; Holleywell, P.

2016-04-01

This paper is framed within the area of medical image processing and aims to present the process of installation, configuration and implementation of a processing server of medical images (MIPS) in the Fundación Escuela de Medicina Nuclear located in Mendoza, Argentina (FUESMEN). It has been developed in the Gabinete de Tecnologia Médica (GA.TE.ME), Facultad de Ingeniería-Universidad Nacional de San Juan. MIPS is a software that using the DICOM standard, can receive medical imaging studies of different modalities or viewing stations, then it executes algorithms and finally returns the results to other devices. To achieve the objectives previously mentioned, preliminary tests were conducted in the laboratory. More over, tools were remotely installed in clinical enviroment. The appropiate protocols for setting up and using them in different services were established once defined those suitable algorithms. Finally, it’s important to focus on the implementation and training that is provided in FUESMEN, using nuclear medicine quality control processes. Results on implementation are exposed in this work.

A Perceptually Weighted Rank Correlation Indicator for Objective Image Quality Assessment

NASA Astrophysics Data System (ADS)

Wu, Qingbo; Li, Hongliang; Meng, Fanman; Ngan, King N.

2018-05-01

In the field of objective image quality assessment (IQA), the Spearman's $\\rho$ and Kendall's $\\tau$ are two most popular rank correlation indicators, which straightforwardly assign uniform weight to all quality levels and assume each pair of images are sortable. They are successful for measuring the average accuracy of an IQA metric in ranking multiple processed images. However, two important perceptual properties are ignored by them as well. Firstly, the sorting accuracy (SA) of high quality images are usually more important than the poor quality ones in many real world applications, where only the top-ranked images would be pushed to the users. Secondly, due to the subjective uncertainty in making judgement, two perceptually similar images are usually hardly sortable, whose ranks do not contribute to the evaluation of an IQA metric. To more accurately compare different IQA algorithms, we explore a perceptually weighted rank correlation indicator in this paper, which rewards the capability of correctly ranking high quality images, and suppresses the attention towards insensitive rank mistakes. More specifically, we focus on activating `valid' pairwise comparison towards image quality, whose difference exceeds a given sensory threshold (ST). Meanwhile, each image pair is assigned an unique weight, which is determined by both the quality level and rank deviation. By modifying the perception threshold, we can illustrate the sorting accuracy with a more sophisticated SA-ST curve, rather than a single rank correlation coefficient. The proposed indicator offers a new insight for interpreting visual perception behaviors. Furthermore, the applicability of our indicator is validated in recommending robust IQA metrics for both the degraded and enhanced image data.

Coupled dictionary learning for joint MR image restoration and segmentation

NASA Astrophysics Data System (ADS)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

Multimodal Imaging and Lighting Bias Correction for Improved μPAD-based Water Quality Monitoring via Smartphones

NASA Astrophysics Data System (ADS)

McCracken, Katherine E.; Angus, Scott V.; Reynolds, Kelly A.; Yoon, Jeong-Yeol

2016-06-01

Smartphone image-based sensing of microfluidic paper analytical devices (μPADs) offers low-cost and mobile evaluation of water quality. However, consistent quantification is a challenge due to variable environmental, paper, and lighting conditions, especially across large multi-target μPADs. Compensations must be made for variations between images to achieve reproducible results without a separate lighting enclosure. We thus developed a simple method using triple-reference point normalization and a fast-Fourier transform (FFT)-based pre-processing scheme to quantify consistent reflected light intensity signals under variable lighting and channel conditions. This technique was evaluated using various light sources, lighting angles, imaging backgrounds, and imaging heights. Further testing evaluated its handle of absorbance, quenching, and relative scattering intensity measurements from assays detecting four water contaminants - Cr(VI), total chlorine, caffeine, and E. coli K12 - at similar wavelengths using the green channel of RGB images. Between assays, this algorithm reduced error from μPAD surface inconsistencies and cross-image lighting gradients. Although the algorithm could not completely remove the anomalies arising from point shadows within channels or some non-uniform background reflections, it still afforded order-of-magnitude quantification and stable assay specificity under these conditions, offering one route toward improving smartphone quantification of μPAD assays for in-field water quality monitoring.

Spectral CT imaging in patients with Budd-Chiari syndrome: investigation of image quality.

PubMed

Su, Lei; Dong, Junqiang; Sun, Qiang; Liu, Jie; Lv, Peijie; Hu, Lili; Yan, Liangliang; Gao, Jianbo

2014-11-01

To assess the image quality of monochromatic imaging from spectral CT in patients with Budd-Chiari syndrome (BCS), fifty patients with BCS underwent spectral CT to generate conventional 140 kVp polychromatic images (group A) and monochromatic images, with energy levels from 40 to 80, 40 + 70, and 50 + 70 keV fusion images (group B) during the portal venous phase (PVP) and the hepatic venous phase (HVP). Two-sample t tests compared vessel-to-liver contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the portal vein (PV), hepatic vein (HV), inferior vena cava. Readers' subjective evaluations of the image quality were recorded. The highest SNR values in group B were distributed at 50 keV; the highest CNR values in group B were distributed at 40 keV. The higher CNR values and SNR values were obtained though PVP of PV (SNR 18.39 ± 6.13 vs. 10.56 ± 3.31, CNR 7.81 ± 3.40 vs. 3.58 ± 1.31) and HVP of HV (3.89 ± 2.08 vs. 1.27 ± 1.55) in the group B; the lower image noise for group B was at 70 keV and 50 + 70 keV (15.54 ± 8.39 vs. 18.40 ± 4.97, P = 0.0004 and 18.97 ± 7.61 vs. 18.40 ± 4.97, P = 0.0691); the results show that the 50 + 70 keV fusion image quality was better than that in group A. Monochromatic energy levels of 40-70, 40 + 70, and 50 + 70 keV fusion image can increase vascular contrast and that will be helpful for the diagnosis of BCS, we select the 50 + 70 keV fusion image to acquire the best BCS images.

Reducing radiation dose without compromising image quality in preoperative perforator flap imaging with CTA using ASIR technology.

PubMed

Niumsawatt, Vachara; Debrotwir, Andrew N; Rozen, Warren Matthew

2014-01-01

Computed tomographic angiography (CTA) has become a mainstay in preoperative perforator flap planning in the modern era of reconstructive surgery. However, the increased use of CTA does raise the concern of radiation exposure to patients. Several techniques have been developed to decrease radiation dosage without compromising image quality, with varying results. The most recent advance is in the improvement of image reconstruction using an adaptive statistical iterative reconstruction (ASIR) algorithm. We sought to evaluate the image quality of ASIR in preoperative deep inferior epigastric perforator (DIEP) flap surgery, through a direct comparison with conventional filtered back projection (FBP) images. A prospective review of 60 consecutive ASIR and 60 consecutive FBP CTA images using similar protocol (except for radiation dosage) was undertaken, analyzed by 2 independent reviewers. In both groups, we were able to accurately identify axial arteries and their perforators. Subjective analysis of image quality demonstrated no statistically significant difference between techniques. ASIR can thus be used for preoperative imaging with similar image quality to FBP, but with a 60% reduction in radiation delivery to patients.

Dosimetry and image quality assessment in a direct radiography system

PubMed Central

Oliveira, Bruno Beraldo; de Oliveira, Marcio Alves; Paixão, Lucas; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

2014-01-01

Objective To evaluate the mean glandular dose with a solid state detector and the image quality in a direct radiography system, utilizing phantoms. Materials and Methods Irradiations were performed with automatic exposure control and polymethyl methacrylate slabs with different thicknesses to calculate glandular dose values. The image quality was evaluated by means of the structures visualized on the images of the phantoms. Results Considering the uncertainty of the measurements, the mean glandular dose results are in agreement with the values provided by the equipment and with internationally adopted reference levels. Results obtained from images of the phantoms were in agreement with the reference values. Conclusion The present study contributes to verify the equipment conformity as regards dose values and image quality. PMID:25741119

Can image enhancement allow radiation dose to be reduced whilst maintaining the perceived diagnostic image quality required for coronary angiography?

PubMed Central

Joshi, Anuja; Gislason-Lee, Amber J; Keeble, Claire; Sivananthan, Uduvil M

2017-01-01

Objective: The aim of this research was to quantify the reduction in radiation dose facilitated by image processing alone for percutaneous coronary intervention (PCI) patient angiograms, without reducing the perceived image quality required to confidently make a diagnosis. Methods: Incremental amounts of image noise were added to five PCI angiograms, simulating the angiogram as having been acquired at corresponding lower dose levels (10–89% dose reduction). 16 observers with relevant experience scored the image quality of these angiograms in 3 states—with no image processing and with 2 different modern image processing algorithms applied. These algorithms are used on state-of-the-art and previous generation cardiac interventional X-ray systems. Ordinal regression allowing for random effects and the delta method were used to quantify the dose reduction possible by the processing algorithms, for equivalent image quality scores. Results: Observers rated the quality of the images processed with the state-of-the-art and previous generation image processing with a 24.9% and 15.6% dose reduction, respectively, as equivalent in quality to the unenhanced images. The dose reduction facilitated by the state-of-the-art image processing relative to previous generation processing was 10.3%. Conclusion: Results demonstrate that statistically significant dose reduction can be facilitated with no loss in perceived image quality using modern image enhancement; the most recent processing algorithm was more effective in preserving image quality at lower doses. Advances in knowledge: Image enhancement was shown to maintain perceived image quality in coronary angiography at a reduced level of radiation dose using computer software to produce synthetic images from real angiograms simulating a reduction in dose. PMID:28124572

Identification of suitable fundus images using automated quality assessment methods.

PubMed

Şevik, Uğur; Köse, Cemal; Berber, Tolga; Erdöl, Hidayet

2014-04-01

Retinal image quality assessment (IQA) is a crucial process for automated retinal image analysis systems to obtain an accurate and successful diagnosis of retinal diseases. Consequently, the first step in a good retinal image analysis system is measuring the quality of the input image. We present an approach for finding medically suitable retinal images for retinal diagnosis. We used a three-class grading system that consists of good, bad, and outlier classes. We created a retinal image quality dataset with a total of 216 consecutive images called the Diabetic Retinopathy Image Database. We identified the suitable images within the good images for automatic retinal image analysis systems using a novel method. Subsequently, we evaluated our retinal image suitability approach using the Digital Retinal Images for Vessel Extraction and Standard Diabetic Retinopathy Database Calibration level 1 public datasets. The results were measured through the F1 metric, which is a harmonic mean of precision and recall metrics. The highest F1 scores of the IQA tests were 99.60%, 96.50%, and 85.00% for good, bad, and outlier classes, respectively. Additionally, the accuracy of our suitable image detection approach was 98.08%. Our approach can be integrated into any automatic retinal analysis system with sufficient performance scores.

Automated daily quality control analysis for mammography in a multi-unit imaging center.

PubMed

Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

2018-01-01

Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

TH-B-207B-00: Pediatric Image Quality Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

This imaging educational program will focus on solutions to common pediatric image quality optimization challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. One of the most commonly encountered pediatric imaging requirements for the non-specialist hospital is pediatric CT in the emergency room setting. Thus, this educational program will begin with optimization of pediatric CT in the emergency department. Though pediatric cardiovascular MRI may be less common in the non-specialist hospitals, low pediatric volumes and unique cardiovascular anatomy make optimization of these techniques difficult. Therefore, our second speaker willmore » review best practices in pediatric cardiovascular MRI based on experiences from a children’s hospital with a large volume of cardiac patients. Learning Objectives: To learn techniques for optimizing radiation dose and image quality for CT of children in the emergency room setting. To learn solutions for consistently high quality cardiovascular MRI of children.« less

A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

NASA Astrophysics Data System (ADS)

Jobson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

2006-05-01

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally within the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging-terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on the limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

NASA Technical Reports Server (NTRS)

Johnson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

2006-01-01

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

Image quality enhancement for skin cancer optical diagnostics

NASA Astrophysics Data System (ADS)

Bliznuks, Dmitrijs; Kuzmina, Ilona; Bolocko, Katrina; Lihachev, Alexey

2017-12-01

The research presents image quality analysis and enhancement proposals in biophotonic area. The sources of image problems are reviewed and analyzed. The problems with most impact in biophotonic area are analyzed in terms of specific biophotonic task - skin cancer diagnostics. The results point out that main problem for skin cancer analysis is the skin illumination problems. Since it is often not possible to prevent illumination problems, the paper proposes image post processing algorithm - low frequency filtering. Practical results show diagnostic results improvement after using proposed filter. Along that, filter do not reduces diagnostic results' quality for images without illumination defects. Current filtering algorithm requires empirical tuning of filter parameters. Further work needed to test the algorithm in other biophotonic applications and propose automatic filter parameter selection.

Dependence of image quality on image operator and noise for optical diffusion tomography

NASA Astrophysics Data System (ADS)

Chang, Jenghwa; Graber, Harry L.; Barbour, Randall L.

1998-04-01

By applying linear perturbation theory to the radiation transport equation, the inverse problem of optical diffusion tomography can be reduced to a set of linear equations, W(mu) equals R, where W is the weight function, (mu) are the cross- section perturbations to be imaged, and R is the detector readings perturbations. We have studied the dependence of image quality on added systematic error and/or random noise in W and R. Tomographic data were collected from cylindrical phantoms, with and without added inclusions, using Monte Carlo methods. Image reconstruction was accomplished using a constrained conjugate gradient descent method. Result show that accurate images containing few artifacts are obtained when W is derived from a reference states whose optical thickness matches that of the unknown teste medium. Comparable image quality was also obtained for unmatched W, but the location of the target becomes more inaccurate as the mismatch increases. Results of the noise study show that image quality is much more sensitive to noise in W than in R, and the impact of noise increase with the number of iterations. Images reconstructed after pure noise was substituted for R consistently contain large peaks clustered about the cylinder axis, which was an initially unexpected structure. In other words, random input produces a non- random output. This finding suggests that algorithms sensitive to the evolution of this feature could be developed to suppress noise effects.

Body Image and Quality of Life in Adolescents With Craniofacial Conditions

PubMed Central

Crerand, Canice E.; Sarwer, David B.; Kazak, Anne E.; Clarke, Alexandra; DPsych; Rumsey, Nichola

2017-01-01

Objective To evaluate body image in adolescents with and without craniofacial conditions; and to examine relationships between body image and quality of life. Design Case-control design. Setting A pediatric hospital’s craniofacial center and primary care practices. Participants 70 adolescents with visible craniofacial conditions and a demographically-matched sample of 42 adolescents without craniofacial conditions. Main Outcome Measure Adolescents completed measures of quality of life and body image including satisfaction with weight, facial and overall appearance; investment in appearance (importance of appearance to self-worth); and body image disturbance (appearance-related distress and impairment in functioning). Results Adolescents with craniofacial conditions reported lower appearance investment (p < 0.001) and were more likely to report concerns about facial features (p < 0.02) compared to non-affected youth. Females in both groups reported greater investment in appearance, greater body image disturbance, and lower weight satisfaction compared to males (p < 0.01). Within both groups, greater body image disturbance was associated with lower quality of life (p <0.01). The two groups did not differ significantly on measures of quality of life, body image disturbance, or satisfaction with appearance. Conclusions Body image and quality of life in adolescents with craniofacial conditions are similar to non-affected youth. Relationships between body image and quality of life emphasize that appearance perceptions are important to adolescents’ well-being regardless of whether they have a facial disfigurement. Investment in one’s appearance may explain variations in body image satisfaction and serve as an intervention target particularly for females. PMID:26751907

Image Quality Assessment Using the Joint Spatial/Spatial-Frequency Representation

NASA Astrophysics Data System (ADS)

Beghdadi, Azeddine; Iordache, Răzvan

2006-12-01

This paper demonstrates the usefulness of spatial/spatial-frequency representations in image quality assessment by introducing a new image dissimilarity measure based on 2D Wigner-Ville distribution (WVD). The properties of 2D WVD are shortly reviewed, and the important issue of choosing the analytic image is emphasized. The WVD-based measure is shown to be correlated with subjective human evaluation, which is the premise towards an image quality assessor developed on this principle.

Head CT: Image quality improvement of posterior fossa and radiation dose reduction with ASiR - comparative studies of CT head examinations.

PubMed

Guziński, Maciej; Waszczuk, Łukasz; Sąsiadek, Marek J

2016-10-01

To evaluate head CT protocol developed to improve visibility of the brainstem and cerebellum, lower bone-related artefacts in the posterior fossa and maintain patient radioprotection. A paired comparison of head CT performed without Adaptive Statistical Iterative Reconstruction (ASiR) and a clinically indicated follow-up with 40 % ASiR was acquired in one group of 55 patients. Patients were scanned in the axial mode with different scanner settings for the brain and the posterior fossa. Objective image quality analysis was performed with signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Subjective image quality analysis was based on brain structure visibility and evaluation of the artefacts. We achieved 19 % reduction of total DLP and significantly better image quality of posterior fossa structures. SNR for white and grey matter in the cerebellum were 34 % to 36 % higher, respectively, CNR was improved by 142 % and subjective analyses were better for images with ASiR. When imaging parameters are set independently for the brain and the posterior fossa imaging, ASiR has a great potential to improve CT performance: image quality of the brainstem and cerebellum is improved, and radiation dose for the brain as well as total radiation dose are reduced. •With ASiR it is possible to lower radiation dose or improve image quality •Sequentional imaging allows setting scan parameters for brain and posterior-fossa independently •We improved visibility of brainstem structures and decreased radiation dose •Total radiation dose (DLP) was decreased by 19.

Determination of pasture quality using airborne hyperspectral imaging

NASA Astrophysics Data System (ADS)

Pullanagari, R. R.; Kereszturi, G.; Yule, Ian J.; Irwin, M. E.

2015-10-01

Pasture quality is a critical determinant which influences animal performance (live weight gain, milk and meat production) and animal health. Assessment of pasture quality is therefore required to assist farmers with grazing planning and management, benchmarking between seasons and years. Traditionally, pasture quality is determined by field sampling which is laborious, expensive and time consuming, and the information is not available in real-time. Hyperspectral remote sensing has potential to accurately quantify biochemical composition of pasture over wide areas in great spatial detail. In this study an airborne imaging spectrometer (AisaFENIX, Specim) was used with a spectral range of 380-2500 nm with 448 spectral bands. A case study of a 600 ha hill country farm in New Zealand is used to illustrate the use of the system. Radiometric and atmospheric corrections, along with automatized georectification of the imagery using Digital Elevation Model (DEM), were applied to the raw images to convert into geocoded reflectance images. Then a multivariate statistical method, partial least squares (PLS), was applied to estimate pasture quality such as crude protein (CP) and metabolisable energy (ME) from canopy reflectance. The results from this study revealed that estimates of CP and ME had a R2 of 0.77 and 0.79, and RMSECV of 2.97 and 0.81 respectively. By utilizing these regression models, spatial maps were created over the imaged area. These pasture quality maps can be used for adopting precision agriculture practices which improves farm profitability and environmental sustainability.

PROPELLER technique to improve image quality of MRI of the shoulder.

PubMed

Dietrich, Tobias J; Ulbrich, Erika J; Zanetti, Marco; Fucentese, Sandro F; Pfirrmann, Christian W A

2011-12-01

The purpose of this article is to evaluate the use of the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) technique for artifact reduction and overall image quality improvement for intermediate-weighted and T2-weighted MRI of the shoulder. One hundred eleven patients undergoing MR arthrography of the shoulder were included. A coronal oblique intermediate-weighted turbo spin-echo (TSE) sequence with fat suppression and a sagittal oblique T2-weighted TSE sequence with fat suppression were obtained without (standard) and with the PROPELLER technique. Scanning time increased from 3 minutes 17 seconds to 4 minutes 17 seconds (coronal oblique plane) and from 2 minutes 52 seconds to 4 minutes 10 seconds (sagittal oblique) using PROPELLER. Two radiologists graded image artifacts, overall image quality, and delineation of several anatomic structures on a 5-point scale (5, no artifact, optimal diagnostic quality; and 1, severe artifacts, diagnostically not usable). The Wilcoxon signed rank test was used to compare the data of the standard and PROPELLER images. Motion artifacts were significantly reduced in PROPELLER images (p < 0.001). Observer 1 rated motion artifacts with diagnostic impairment in one patient on coronal oblique PROPELLER images compared with 33 patients on standard images. Ratings for the sequences with PROPELLER were significantly better for overall image quality (p < 0.001). Observer 1 noted an overall image quality with diagnostic impairment in nine patients on sagittal oblique PROPELLER images compared with 23 patients on standard MRI. The PROPELLER technique for MRI of the shoulder reduces the number of sequences with diagnostic impairment as a result of motion artifacts and increases image quality compared with standard TSE sequences. PROPELLER sequences increase the acquisition time.

Development of quality control and instrumentation performance metrics for diffuse optical spectroscopic imaging instruments in the multi-center clinical environment

NASA Astrophysics Data System (ADS)

Keene, Samuel T.; Cerussi, Albert E.; Warren, Robert V.; Hill, Brian; Roblyer, Darren; Leproux, AnaÑ--s.; Durkin, Amanda F.; O'Sullivan, Thomas D.; Haghany, Hosain; Mantulin, William W.; Tromberg, Bruce J.

2013-03-01

Instrument equivalence and quality control are critical elements of multi-center clinical trials. We currently have five identical Diffuse Optical Spectroscopic Imaging (DOSI) instruments enrolled in the American College of Radiology Imaging Network (ACRIN, #6691) trial located at five academic clinical research sites in the US. The goal of the study is to predict the response of breast tumors to neoadjuvant chemotherapy in 60 patients. In order to reliably compare DOSI measurements across different instruments, operators and sites, we must be confident that the data quality is comparable. We require objective and reliable methods for identifying, correcting, and rejecting low quality data. To achieve this goal, we developed and tested an automated quality control algorithm that rejects data points below the instrument noise floor, improves tissue optical property recovery, and outputs a detailed data quality report. Using a new protocol for obtaining dark-noise data, we applied the algorithm to ACRIN patient data and successfully improved the quality of recovered physiological data in some cases.

Prediction of Viking lander camera image quality

NASA Technical Reports Server (NTRS)

Huck, F. O.; Burcher, E. E.; Jobson, D. J.; Wall, S. D.

1976-01-01

Formulations are presented that permit prediction of image quality as a function of camera performance, surface radiance properties, and lighting and viewing geometry. Predictions made for a wide range of surface radiance properties reveal that image quality depends strongly on proper camera dynamic range command and on favorable lighting and viewing geometry. Proper camera dynamic range commands depend mostly on the surface albedo that will be encountered. Favorable lighting and viewing geometries depend mostly on lander orientation with respect to the diurnal sun path over the landing site, and tend to be independent of surface albedo and illumination scattering function. Side lighting with low sun elevation angles (10 to 30 deg) is generally favorable for imaging spatial details and slopes, whereas high sun elevation angles are favorable for measuring spectral reflectances.

Synthesized view comparison method for no-reference 3D image quality assessment

NASA Astrophysics Data System (ADS)

Luo, Fangzhou; Lin, Chaoyi; Gu, Xiaodong; Ma, Xiaojun

2018-04-01

We develop a no-reference image quality assessment metric to evaluate the quality of synthesized view rendered from the Multi-view Video plus Depth (MVD) format. Our metric is named Synthesized View Comparison (SVC), which is designed for real-time quality monitoring at the receiver side in a 3D-TV system. The metric utilizes the virtual views in the middle which are warped from left and right views by Depth-image-based rendering algorithm (DIBR), and compares the difference between the virtual views rendered from different cameras by Structural SIMilarity (SSIM), a popular 2D full-reference image quality assessment metric. The experimental results indicate that our no-reference quality assessment metric for the synthesized images has competitive prediction performance compared with some classic full-reference image quality assessment metrics.

Achieving performance breakthroughs in an HMO business process through quality planning.

PubMed

Hanan, K B

1993-01-01

Kaiser Permanente's Georgia Region commissioned a quality planning team to design a new process to improve payments to its suppliers and vendors. The result of the team's effort was a 73 percent reduction in cycle time. This team's experiences point to the advantages of process redesign as a quality planning model, as well as some general guidelines for its most effective use in teams. If quality planning project teams are carefully configured, sufficiently expert in the existing process, and properly supported by management, organizations can achieve potentially dramatic improvements in process performance using this approach.

Radiologists' confidence in detecting abnormalities on chest images and their subjective judgments of image quality

NASA Astrophysics Data System (ADS)

King, Jill L.; Gur, David; Rockette, Howard E.; Curtin, Hugh D.; Obuchowski, Nancy A.; Thaete, F. Leland; Britton, Cynthia A.; Metz, Charles E.

1991-07-01

The relationship between subjective judgments of image quality for the performance of specific detection tasks and radiologists' confidence level in arriving at correct diagnoses was investigated in two studies in which 12 readers, using a total of three different display environments, interpreted a series of 300 PA chest images. The modalities used were conventional films, laser-printed films, and high-resolution CRT display of digitized images. For the detection of interstitial disease, nodules, and pneumothoraces, there was no statistically significant correlation (Spearman rho) between subjective ratings of quality and radiologists' confidence in detecting these abnormalities. However, in each study, for all modalities and all readers but one, a small but statistically significant correlation was found between the radiologists' ability to correctly and confidently rule out interstitial disease and their subjective ratings of image quality.

Comparison of image quality and radiation exposure from C-arm fluoroscopes when used for imaging the spine.

PubMed

Prasarn, Mark L; Coyne, Ellen; Schreck, Michael; Rodgers, Jamie D; Rechtine, Glenn R

2013-07-15

Cadaveric imaging study. We sought to compare the fluoroscopic images produced by 4 different fluoroscopes for image quality and radiation exposure when used for imaging the spine. There are no previous published studies comparing mobile C-arm machines commonly used in clinical practice for imaging the spine. Anterior-posterior and lateral images of the cervical, thoracic, and lumbar spine were obtained from a cadaver placed supine on a radiolucent table. The fluoroscopy units used for the study included (1) GE OEC 9900 Elite (2010 model; General Electric Healthcare, Waukesha, WI), (2) Philips BV Pulsera (2009 model; Philips Healthcare, Andover, MA), (3) Philips BV Pulsera (2010 model; Philips Healthcare, Andover, MA), and (4) Siemens Arcadis Avantic (2010 model; Siemens Medical Solutions, Malvern, PA). The images were then downloaded, placed into a randomizer program, and evaluated by a group of spine surgeons and neuroradiologists independently. The reviewers, who were blinded to the fluoroscope the images were from, ranked them from best to worst using a numeric system. In addition, the images were rated according to a quality scale from 1 to 5, with 1 representing the best image quality. The radiation exposure level for the fluoroscopy units was also compared and was based on energy emission. According to the mean values for rank, the following order of best to worst was observed: (1) GE OEC > (2) Philips 2010 > (3) Philips 2009 > (4) Siemans. The exact same order was found when examining the image quality ratings. When comparing the radiation exposure level difference, it was observed that the OEC was the lowest, and there was a minimum 30% decrease in energy emission from the OEC versus the other C-arms studied. This is the first time that the spine image quality and radiation exposure of commonly used C-arm machines have been compared. The OEC was ranked the best, produced the best quality images, and had the least amount of radiation.

Evaluation of image quality of MRI data for brain tumor surgery

NASA Astrophysics Data System (ADS)

Heckel, Frank; Arlt, Felix; Geisler, Benjamin; Zidowitz, Stephan; Neumuth, Thomas

2016-03-01

3D medical images are important components of modern medicine. Their usefulness for the physician depends on their quality, though. Only high-quality images allow accurate and reproducible diagnosis and appropriate support during treatment. We have analyzed 202 MRI images for brain tumor surgery in a retrospective study. Both an experienced neurosurgeon and an experienced neuroradiologist rated each available image with respect to its role in the clinical workflow, its suitability for this specific role, various image quality characteristics, and imaging artifacts. Our results show that MRI data acquired for brain tumor surgery does not always fulfill the required quality standards and that there is a significant disagreement between the surgeon and the radiologist, with the surgeon being more critical. Noise, resolution, as well as the coverage of anatomical structures were the most important criteria for the surgeon, while the radiologist was mainly disturbed by motion artifacts.

Image quality specification and maintenance for airborne SAR

NASA Astrophysics Data System (ADS)

Clinard, Mark S.

2004-08-01

Specification, verification, and maintenance of image quality over the lifecycle of an operational airborne SAR begin with the specification for the system itself. Verification of image quality-oriented specification compliance can be enhanced by including a specification requirement that a vendor provide appropriate imagery at the various phases of the system life cycle. The nature and content of the imagery appropriate for each stage of the process depends on the nature of the test, the economics of collection, and the availability of techniques to extract the desired information from the data. At the earliest lifecycle stages, Concept and Technology Development (CTD) and System Development and Demonstration (SDD), the test set could include simulated imagery to demonstrate the mathematical and engineering concepts being implemented thus allowing demonstration of compliance, in part, through simulation. For Initial Operational Test and Evaluation (IOT&E), imagery collected from precisely instrumented test ranges and targets of opportunity consisting of a priori or a posteriori ground-truthed cultural and natural features are of value to the analysis of product quality compliance. Regular monitoring of image quality is possible using operational imagery and automated metrics; more precise measurements can be performed with imagery of instrumented scenes, when available. A survey of image quality measurement techniques is presented along with a discussion of the challenges of managing an airborne SAR program with the scarce resources of time, money, and ground-truthed data. Recommendations are provided that should allow an improvement in the product quality specification and maintenance process with a minimal increase in resource demands on the customer, the vendor, the operational personnel, and the asset itself.

Head CT: Image quality improvement with ASIR-V using a reduced radiation dose protocol for children.

PubMed

Kim, Hyun Gi; Lee, Ho-Joon; Lee, Seung-Koo; Kim, Hyun Ji; Kim, Myung-Joon

2017-09-01

To investigate the quality of images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V), using pediatric head CT protocols. A phantom was scanned at decreasing 20% mA intervals using our standard pediatric head CT protocols. Each study was then reconstructed at 10% ASIR-V intervals. After the phantom study, we reduced mA by 10% in the protocol for <3-year-old patients and applied 30% ASIR-V and by 30% in the protocol for 3- to 15-year-old patients and applied 40% ASIR-V. Increasing the percentage of ASIR-V resulted in lower noise and higher contrast-to-noise ratio (CNR) and preserved spatial resolution in the phantom study. Compared to a conventional-protocol, reduced-dose protocol with ASIR-V achieved 12.8% to 34.0% of dose reduction and showed images of lower noise (9.22 vs. 10.73, P = 0.043) and higher CNR in different levels (centrum semiovale, 2.14 vs. 1.52, P = 0.003; basal ganglia, 1.46 vs. 1.07, P = 0.001; and cerebellum, 2.18 vs. 1.33, P < 0.001). Qualitative analysis showed higher gray-white matter differentiation and sharpness and preserved overall diagnostic quality in the images with ASIR-V. Use of ASIR-V allowed a 12.8% to 34.0% dose reduction in each age group with potential to improve image quality. • It is possible to reduce radiation dose and improve image quality with ASIR-V. • We improved noise and CNR and decreased radiation dose. • Sharpness improved with ASIR-V. • Total radiation dose was decreased by 12.8% to 34.0%.

Improving quality of arterial spin labeling MR imaging at 3 Tesla with a 32-channel coil and parallel imaging.

PubMed

Ferré, Jean-Christophe; Petr, Jan; Bannier, Elise; Barillot, Christian; Gauvrit, Jean-Yves

2012-05-01

To compare 12-channel and 32-channel phased-array coils and to determine the optimal parallel imaging (PI) technique and factor for brain perfusion imaging using Pulsed Arterial Spin labeling (PASL) at 3 Tesla (T). Twenty-seven healthy volunteers underwent 10 different PASL perfusion PICORE Q2TIPS scans at 3T using 12-channel and 32-channel coils without PI and with GRAPPA or mSENSE using factor 2. PI with factor 3 and 4 were used only with the 32-channel coil. Visual quality was assessed using four parameters. Quantitative analyses were performed using temporal noise, contrast-to-noise and signal-to-noise ratios (CNR, SNR). Compared with 12-channel acquisition, the scores for 32-channel acquisition were significantly higher for overall visual quality, lower for noise and higher for SNR and CNR. With the 32-channel coil, artifact compromise achieved the best score with PI factor 2. Noise increased, SNR and CNR decreased with PI factor. However mSENSE 2 scores were not always significantly different from acquisition without PI. For PASL at 3T, the 32-channel coil at 3T provided better quality than the 12-channel coil. With the 32-channel coil, mSENSE 2 seemed to offer the best compromise for decreasing artifacts without significantly reducing SNR, CNR. Copyright © 2012 Wiley Periodicals, Inc.

Study of a water quality imager for coastal zone missions

NASA Technical Reports Server (NTRS)

Staylor, W. F.; Harrison, E. F.; Wessel, V. W.

1975-01-01

The present work surveys water quality user requirements and then determines the general characteristics of an orbiting imager (the Applications Explorer, or AE) dedicated to the measurement of water quality, which could be used as a low-cost means of testing advanced imager concepts and assessing the ability of imager techniques to meet the goals of a comprehensive water quality monitoring program. The proposed imager has four spectral bands, a spatial resolution of 25 meters, and swath width of 36 km with a pointing capability of 330 km. Silicon photodetector arrays, pointing systems, and several optical features are included. A nominal orbit of 500 km altitude at an inclination of 50 deg is recommended.

High-field open versus short-bore magnetic resonance imaging of the spine: a randomized controlled comparison of image quality.

PubMed

Enders, Judith; Rief, Matthias; Zimmermann, Elke; Asbach, Patrick; Diederichs, Gerd; Wetz, Christoph; Siebert, Eberhard; Wagner, Moritz; Hamm, Bernd; Dewey, Marc

2013-01-01

The purpose of the present study was to compare the image quality of spinal magnetic resonance (MR) imaging performed on a high-field horizontal open versus a short-bore MR scanner in a randomized controlled study setup. Altogether, 93 (80% women, mean age 53) consecutive patients underwent spine imaging after random assignement to a 1-T horizontal open MR scanner with a vertical magnetic field or a 1.5-T short-bore MR scanner. This patient subset was part of a larger cohort. Image quality was assessed by determining qualitative parameters, signal-to-noise (SNR) and contrast-to-noise ratios (CNR), and quantitative contour sharpness. The image quality parameters were higher for short-bore MR imaging. Regarding all sequences, the relative differences were 39% for the mean overall qualitative image quality, 53% for the mean SNR values, and 34-37% for the quantitative contour sharpness (P<0.0001). The CNR values were also higher for images obtained with the short-bore MR scanner. No sequence was of very poor (nondiagnostic) image quality. Scanning times were significantly longer for examinations performed on the open MR scanner (mean: 32±22 min versus 20±9 min; P<0.0001). In this randomized controlled comparison of spinal MR imaging with an open versus a short-bore scanner, short-bore MR imaging revealed considerably higher image quality with shorter scanning times. ClinicalTrials.gov NCT00715806.

High-Field Open versus Short-Bore Magnetic Resonance Imaging of the Spine: A Randomized Controlled Comparison of Image Quality

PubMed Central

Zimmermann, Elke; Asbach, Patrick; Diederichs, Gerd; Wetz, Christoph; Siebert, Eberhard; Wagner, Moritz; Hamm, Bernd; Dewey, Marc

2013-01-01

Background The purpose of the present study was to compare the image quality of spinal magnetic resonance (MR) imaging performed on a high-field horizontal open versus a short-bore MR scanner in a randomized controlled study setup. Methods Altogether, 93 (80% women, mean age 53) consecutive patients underwent spine imaging after random assignement to a 1-T horizontal open MR scanner with a vertical magnetic field or a 1.5-T short-bore MR scanner. This patient subset was part of a larger cohort. Image quality was assessed by determining qualitative parameters, signal-to-noise (SNR) and contrast-to-noise ratios (CNR), and quantitative contour sharpness. Results The image quality parameters were higher for short-bore MR imaging. Regarding all sequences, the relative differences were 39% for the mean overall qualitative image quality, 53% for the mean SNR values, and 34–37% for the quantitative contour sharpness (P<0.0001). The CNR values were also higher for images obtained with the short-bore MR scanner. No sequence was of very poor (nondiagnostic) image quality. Scanning times were significantly longer for examinations performed on the open MR scanner (mean: 32±22 min versus 20±9 min; P<0.0001). Conclusions In this randomized controlled comparison of spinal MR imaging with an open versus a short-bore scanner, short-bore MR imaging revealed considerably higher image quality with shorter scanning times. Trial Registration ClinicalTrials.gov NCT00715806 PMID:24391767

Body image and quality of life in a Spanish population

PubMed Central

Lobera, Ignacio Jáuregui; Ríos, Patricia Bolaños

2011-01-01

Purpose The aim of the current study was to analyze the psychometric properties, factor structure, and internal consistency of the Spanish version of the Body Image Quality of Life Inventory (BIQLI-SP) as well as its test–retest reliability. Further objectives were to analyze different relationships with key dimensions of psychosocial functioning (ie, self-esteem, presence of psychopathological symptoms, eating and body image-related problems, and perceived stress) and to evaluate differences in body image quality of life due to gender. Patients and methods The sample comprised 417 students without any psychiatric history, recruited from the Pablo de Olavide University and the University of Seville. There were 140 men (33.57%) and 277 women (66.43%), and the mean age was 21.62 years (standard deviation = 5.12). After obtaining informed consent from all participants, the following questionnaires were administered: BIQLI, Eating Disorder Inventory-2 (EDI-2), Perceived Stress Questionnaire (PSQ), Self-Esteem Scale (SES), and Symptom Checklist-90-Revised (SCL-90-R). Results The BIQLI-SP shows adequate psychometric properties, and it may be useful to determine the body image quality of life in different physical conditions. A more positive body image quality of life is associated with better self-esteem, better psychological wellbeing, and fewer eating-related dysfunctional attitudes, this being more evident among women. Conclusion The BIQLI-SP may be useful to determine the body image quality of life in different contexts with regard to dermatology, cosmetic and reconstructive surgery, and endocrinology, among others. In these fields of study, a new trend has emerged to assess body image-related quality of life. PMID:21403794

High-resolution T2-weighted abdominal magnetic resonance imaging using respiratory triggering: impact of butylscopolamine on image quality.

PubMed

Wagner, M; Klessen, C; Rief, M; Elgeti, T; Taupitz, M; Hamm, B; Asbach, P

2008-05-01

Respiratory triggering allows the acquisition of high-resolution magnetic resonance (MR) images of the upper abdomen. However, the depiction of organs close to the gastrointestinal tract can be considerably impaired by ghosting artifacts and blurring caused by bowel peristalsis. To evaluate the effect of gastrointestinal motion suppression by intramuscular butylscopolamine administration on the image quality of a respiratory-triggered T2-weighted turbo spin-echo (T2w TSE) sequence of the upper abdomen. Images of 46 patients were retrospectively analyzed. Twenty-four patients had received intramuscular injection of 40 mg butylscopolamine immediately before MR imaging. Fourteen of the 24 patients in the butylscopolamine group underwent repeat imaging after a mean of 29 min. Quantitative analysis of the ghosting artifacts was done by measuring signal intensities in regions of interest placed in air anterior to the patient. In addition, image quality was assessed qualitatively by two radiologists by consensus. Spasmolytic medication with butylscopolamine reduced ghosting artifacts and significantly improved image quality of the respiratory-triggered T2w TSE sequence. The most pronounced effect of butylscopolamine administration on image quality was found for the pancreas and the left hepatic lobe. The rate of examinations with excellent or good depiction of the pancreas and the left hepatic lobe in the group without premedication and in the butylscopolamine group was 55% vs. 96% (pancreatic head), 35% vs. 88% (pancreatic body), 43% vs. 96% (pancreatic tail), and 45% vs. 83% (left hepatic lobe), respectively. Regarding the duration of the effect of intramuscular butylscopolamine, repeat imaging after a mean of 29 min did not result in a significant deterioration of image quality. Intramuscular butylscopolamine administration significantly improves image quality of respiratory-triggered T2-weighted abdominal MR imaging by persistent reduction of peristaltic artifacts. MR

Face detection on distorted images using perceptual quality-aware features

NASA Astrophysics Data System (ADS)

Gunasekar, Suriya; Ghosh, Joydeep; Bovik, Alan C.

2014-02-01

We quantify the degradation in performance of a popular and effective face detector when human-perceived image quality is degraded by distortions due to additive white gaussian noise, gaussian blur or JPEG compression. It is observed that, within a certain range of perceived image quality, a modest increase in image quality can drastically improve face detection performance. These results can be used to guide resource or bandwidth allocation in a communication/delivery system that is associated with face detection tasks. A new face detector based on QualHOG features is also proposed that augments face-indicative HOG features with perceptual quality-aware spatial Natural Scene Statistics (NSS) features, yielding improved tolerance against image distortions. The new detector provides statistically significant improvements over a strong baseline on a large database of face images representing a wide range of distortions. To facilitate this study, we created a new Distorted Face Database, containing face and non-face patches from images impaired by a variety of common distortion types and levels. This new dataset is available for download and further experimentation at www.ideal.ece.utexas.edu/˜suriya/DFD/.

Radiation dose and image quality for paediatric interventional cardiology

NASA Astrophysics Data System (ADS)

Vano, E.; Ubeda, C.; Leyton, F.; Miranda, P.

2008-08-01

Radiation dose and image quality for paediatric protocols in a biplane x-ray system used for interventional cardiology have been evaluated. Entrance surface air kerma (ESAK) and image quality using a test object and polymethyl methacrylate (PMMA) phantoms have been measured for the typical paediatric patient thicknesses (4-20 cm of PMMA). Images from fluoroscopy (low, medium and high) and cine modes have been archived in digital imaging and communications in medicine (DICOM) format. Signal-to-noise ratio (SNR), figure of merit (FOM), contrast (CO), contrast-to-noise ratio (CNR) and high contrast spatial resolution (HCSR) have been computed from the images. Data on dose transferred to the DICOM header have been used to test the values of the dosimetric display at the interventional reference point. ESAK for fluoroscopy modes ranges from 0.15 to 36.60 µGy/frame when moving from 4 to 20 cm PMMA. For cine, these values range from 2.80 to 161.10 µGy/frame. SNR, FOM, CO, CNR and HCSR are improved for high fluoroscopy and cine modes and maintained roughly constant for the different thicknesses. Cumulative dose at the interventional reference point resulted 25-45% higher than the skin dose for the vertical C-arm (depending of the phantom thickness). ESAK and numerical image quality parameters allow the verification of the proper setting of the x-ray system. Knowing the increases in dose per frame when increasing phantom thicknesses together with the image quality parameters will help cardiologists in the good management of patient dose and allow them to select the best imaging acquisition mode during clinical procedures.

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Angelis, L; Landry, G; Dedes, G

Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBsmore » was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)« less

Image Quality Improvement in Adaptive Optics Scanning Laser Ophthalmoscopy Assisted Capillary Visualization Using B-spline-based Elastic Image Registration

PubMed Central

Uji, Akihito; Ooto, Sotaro; Hangai, Masanori; Arichika, Shigeta; Yoshimura, Nagahisa

2013-01-01

Purpose To investigate the effect of B-spline-based elastic image registration on adaptive optics scanning laser ophthalmoscopy (AO-SLO)-assisted capillary visualization. Methods AO-SLO videos were acquired from parafoveal areas in the eyes of healthy subjects and patients with various diseases. After nonlinear image registration, the image quality of capillary images constructed from AO-SLO videos using motion contrast enhancement was compared before and after B-spline-based elastic (nonlinear) image registration performed using ImageJ. For objective comparison of image quality, contrast-to-noise ratios (CNRS) for vessel images were calculated. For subjective comparison, experienced ophthalmologists ranked images on a 5-point scale. Results All AO-SLO videos were successfully stabilized by elastic image registration. CNR was significantly higher in capillary images stabilized by elastic image registration than in those stabilized without registration. The average ratio of CNR in images with elastic image registration to CNR in images without elastic image registration was 2.10 ± 1.73, with no significant difference in the ratio between patients and healthy subjects. Improvement of image quality was also supported by expert comparison. Conclusions Use of B-spline-based elastic image registration in AO-SLO-assisted capillary visualization was effective for enhancing image quality both objectively and subjectively. PMID:24265796

Defining Quality in Cardiovascular Imaging: A Scientific Statement From the American Heart Association.

PubMed

Shaw, Leslee J; Blankstein, Ron; Jacobs, Jill E; Leipsic, Jonathon A; Kwong, Raymond Y; Taqueti, Viviany R; Beanlands, Rob S B; Mieres, Jennifer H; Flamm, Scott D; Gerber, Thomas C; Spertus, John; Di Carli, Marcelo F

2017-12-01

The aims of the current statement are to refine the definition of quality in cardiovascular imaging and to propose novel methodological approaches to inform the demonstration of quality in imaging in future clinical trials and registries. We propose defining quality in cardiovascular imaging using an analytical framework put forth by the Institute of Medicine whereby quality was defined as testing being safe, effective, patient-centered, timely, equitable, and efficient. The implications of each of these components of quality health care are as essential for cardiovascular imaging as they are for other areas within health care. Our proposed statement may serve as the foundation for integrating these quality indicators into establishing designations of quality laboratory practices and developing standards for value-based payment reform for imaging services. We also include recommendations for future clinical research to fulfill quality aims within cardiovascular imaging, including clinical hypotheses of improving patient outcomes, the importance of health status as an end point, and deferred testing options. Future research should evolve to define novel methods optimized for the role of cardiovascular imaging for detecting disease and guiding treatment and to demonstrate the role of cardiovascular imaging in facilitating healthcare quality. © 2017 American Heart Association, Inc.

Radiation dose optimization in pediatric temporal bone computed tomography: influence of tube tension on image contrast and image quality.

PubMed

Nauer, Claude Bertrand; Zubler, Christoph; Weisstanner, Christian; Stieger, Christof; Senn, Pascal; Arnold, Andreas

2012-03-01

The purpose of this experimental study was to investigate the effect of tube tension reduction on image contrast and image quality in pediatric temporal bone computed tomography (CT). Seven lamb heads with infant-equivalent sizes were scanned repeatedly, using four tube tensions from 140 to 80 kV while the CT-Dose Index (CTDI) was held constant. Scanning was repeated with four CTDI values from 30 to 3 mGy. Image contrast was calculated for the middle ear as the Hounsfield unit (HU) difference between bone and air and for the inner ear as the HU difference between bone and fluid. The influence of tube tension on high-contrast detail delineation was evaluated using a phantom. The subjective image quality of eight middle and inner ear structures was assessed using a 4-point scale (scores 1-2 = insufficient; scores 3-4 = sufficient). Middle and inner ear contrast showed a near linear increase with tube tension reduction (r = -0.94/-0.88) and was highest at 80 kV. Tube tension had no influence on spatial resolution. Subjective image quality analysis showed significantly better scoring at lower tube tensions, with highest image quality at 80 kV. However, image quality improvement was most relevant for low-dose scans. Image contrast in the temporal bone is significantly higher at low tube tensions, leading to a better subjective image quality. Highest contrast and best quality were found at 80 kV. This image quality improvement might be utilized to further reduce the radiation dose in pediatric low-dose CT protocols.

Relationships between body image, sexual satisfaction, and relationship quality in romantic couples.

PubMed

van den Brink, Femke; Vollmann, Manja; Smeets, Monique A M; Hessen, David J; Woertman, Liesbeth

2018-03-08

Previous studies found important associations between body image, sexual satisfaction, and perceived romantic relationship quality, but mainly focused on one individual's perceptions rather than both partners. To take the interdependency of romantic partners into account, the present study examined these associations in romantic couples with a dyadic approach. In a cross-sectional design, 151 Dutch heterosexual couples completed an online survey measuring body image, sexual satisfaction, and perceived relationship quality. Hypotheses were tested using the actor-partner interdependence model (APIM) and an APIM extended with a mediator (APIMeM), with couple members' body image as predictors, couple members' sexual satisfaction as mediators, and couple members' relationship quality as outcomes. Results indicated that within individuals, a more positive body image was linked to higher perceived romantic relationship quality through greater sexual satisfaction. No gender differences were found, implying that body image and sexual satisfaction are equally strongly associated with perceived relationship quality in women and men. Results revealed no associations of an individual's body image and sexual satisfaction with the partner's perceived relationship quality. These findings implicate that interventions focusing on developing and maintaining a positive body image may be helpful in building on a more satisfying sex life and higher perceived relationship quality. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Image quality of mixed convolution kernel in thoracic computed tomography.

PubMed

Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

2016-11-01

The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

Quantitative metrics for assessment of chemical image quality and spatial resolution

DOE PAGES

Kertesz, Vilmos; Cahill, John F.; Van Berkel, Gary J.

2016-02-28

Rationale: Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Methods: We developed two image metrics, viz., chemical image contrast (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and corrected resolving power factor (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest inmore » an image. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. Results: The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. Conclusions: ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system.« less

Quantitative metrics for assessment of chemical image quality and spatial resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kertesz, Vilmos; Cahill, John F.; Van Berkel, Gary J.

Rationale: Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Methods: We developed two image metrics, viz., chemical image contrast (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and corrected resolving power factor (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest inmore » an image. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. Results: The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. Conclusions: ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system.« less

Optimization of image quality and dose for Varian aS500 electronic portal imaging devices (EPIDs).

PubMed

McGarry, C K; Grattan, M W D; Cosgrove, V P

2007-12-07

This study was carried out to investigate whether the electronic portal imaging (EPI) acquisition process could be optimized, and as a result tolerance and action levels be set for the PIPSPro QC-3V phantom image quality assessment. The aim of the optimization process was to reduce the dose delivered to the patient while maintaining a clinically acceptable image quality. This is of interest when images are acquired in addition to the planned patient treatment, rather than images being acquired using the treatment field during a patient's treatment. A series of phantoms were used to assess image quality for different acquisition settings relative to the baseline values obtained following acceptance testing. Eight Varian aS500 EPID systems on four matched Varian 600C/D linacs and four matched Varian 2100C/D linacs were compared for consistency of performance and images were acquired at the four main orthogonal gantry angles. Images were acquired using a 6 MV beam operating at 100 MU min(-1) and the low-dose acquisition mode. Doses used in the comparison were measured using a Farmer ionization chamber placed at d(max) in solid water. The results demonstrated that the number of reset frames did not have any influence on the image contrast, but the number of frame averages did. The expected increase in noise with corresponding decrease in contrast was also observed when reducing the number of frame averages. The optimal settings for the low-dose acquisition mode with respect to image quality and dose were found to be one reset frame and three frame averages. All patients at the Northern Ireland Cancer Centre are now imaged using one reset frame and three frame averages in the 6 MV 100 MU min(-1) low-dose acquisition mode. Routine EPID QC contrast tolerance (+/-10) and action (+/-20) levels using the PIPSPro phantom based around expected values of 190 (Varian 600C/D) and 225 (Varian 2100C/D) have been introduced. The dose at dmax from electronic portal imaging has been

Predicting perceptual quality of images in realistic scenario using deep filter banks

NASA Astrophysics Data System (ADS)

Zhang, Weixia; Yan, Jia; Hu, Shiyong; Ma, Yang; Deng, Dexiang

2018-03-01

Classical image perceptual quality assessment models usually resort to natural scene statistic methods, which are based on an assumption that certain reliable statistical regularities hold on undistorted images and will be corrupted by introduced distortions. However, these models usually fail to accurately predict degradation severity of images in realistic scenarios since complex, multiple, and interactive authentic distortions usually appear on them. We propose a quality prediction model based on convolutional neural network. Quality-aware features extracted from filter banks of multiple convolutional layers are aggregated into the image representation. Furthermore, an easy-to-implement and effective feature selection strategy is used to further refine the image representation and finally a linear support vector regression model is trained to map image representation into images' subjective perceptual quality scores. The experimental results on benchmark databases present the effectiveness and generalizability of the proposed model.

Evaluations of UltraiQ software for objective ultrasound image quality assessment using images from a commercial scanner.

PubMed

Long, Zaiyang; Tradup, Donald J; Stekel, Scott F; Gorny, Krzysztof R; Hangiandreou, Nicholas J

2018-03-01

We evaluated a commercially available software package that uses B-mode images to semi-automatically measure quantitative metrics of ultrasound image quality, such as contrast response, depth of penetration (DOP), and spatial resolution (lateral, axial, and elevational). Since measurement of elevational resolution is not a part of the software package, we achieved it by acquiring phantom images with transducers tilted at 45 degrees relative to the phantom. Each measurement was assessed in terms of measurement stability, sensitivity, repeatability, and semi-automated measurement success rate. All assessments were performed on a GE Logiq E9 ultrasound system with linear (9L or 11L), curved (C1-5), and sector (S1-5) transducers, using a CIRS model 040GSE phantom. In stability tests, the measurements of contrast, DOP, and spatial resolution remained within a ±10% variation threshold in 90%, 100%, and 69% of cases, respectively. In sensitivity tests, contrast, DOP, and spatial resolution measurements followed the expected behavior in 100%, 100%, and 72% of cases, respectively. In repeatability testing, intra- and inter-individual coefficients of variations were equal to or less than 3.2%, 1.3%, and 4.4% for contrast, DOP, and spatial resolution (lateral and axial), respectively. The coefficients of variation corresponding to the elevational resolution test were all within 9.5%. Overall, in our assessment, the evaluated package performed well for objective and quantitative assessment of the above-mentioned image qualities under well-controlled acquisition conditions. We are finding it to be useful for various clinical ultrasound applications including performance comparison between scanners from different vendors. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Image quality assessment by preprocessing and full reference model combination

NASA Astrophysics Data System (ADS)

Bianco, S.; Ciocca, G.; Marini, F.; Schettini, R.

2009-01-01

This paper focuses on full-reference image quality assessment and presents different computational strategies aimed to improve the robustness and accuracy of some well known and widely used state of the art models, namely the Structural Similarity approach (SSIM) by Wang and Bovik and the S-CIELAB spatial-color model by Zhang and Wandell. We investigate the hypothesis that combining error images with a visual attention model could allow a better fit of the psycho-visual data of the LIVE Image Quality assessment Database Release 2. We show that the proposed quality assessment metric better correlates with the experimental data.

Image quality and stability of image-guided radiotherapy (IGRT) devices: A comparative study.

PubMed

Stock, Markus; Pasler, Marlies; Birkfellner, Wolfgang; Homolka, Peter; Poetter, Richard; Georg, Dietmar

2009-10-01

Our aim was to implement standards for quality assurance of IGRT devices used in our department and to compare their performances with that of a CT simulator. We investigated image quality parameters for three devices over a period of 16months. A multislice CT was used as a benchmark and results related to noise, spatial resolution, low contrast visibility (LCV) and uniformity were compared with a cone beam CT (CBCT) at a linac and simulator. All devices performed well in terms of LCV and, in fact, exceeded vendor specifications. MTF was comparable between CT and linac CBCT. Integral nonuniformity was, on average, 0.002 for the CT and 0.006 for the linac CBCT. Uniformity, LCV and MTF varied depending on the protocols used for the linac CBCT. Contrast-to-noise ratio was an average of 51% higher for the CT than for the linac and simulator CBCT. No significant time trend was observed and tolerance limits were implemented. Reasonable differences in image quality between CT and CBCT were observed. Further research and development are necessary to increase image quality of commercially available CBCT devices in order for them to serve the needs for adaptive and/or online planning.

Locally Enhanced Image Quality with Tunable Hybrid Metasurfaces

NASA Astrophysics Data System (ADS)

Shchelokova, Alena V.; Slobozhanyuk, Alexey P.; Melchakova, Irina V.; Glybovski, Stanislav B.; Webb, Andrew G.; Kivshar, Yuri S.; Belov, Pavel A.

2018-01-01

Metasurfaces represent a new paradigm in artificial subwavelength structures due to their potential to overcome many challenges typically associated with bulk metamaterials. The ability to make very thin structures and change their properties dynamically makes metasurfaces an exceptional meta-optics platform for engineering advanced electromagnetic and photonic metadevices. Here, we suggest and demonstrate experimentally a tunable metasurface capable of enhancing significantly the local image quality in magnetic resonance imaging. We present a design of the hybrid metasurface based on electromagnetically coupled dielectric and metallic elements. We demonstrate how to tailor the spectral characteristics of the metasurface eigenmodes by changing dynamically the effective permittivity of the structure. By maximizing a coupling between metasurface eigenmodes and transmitted and received fields in the magnetic resonance imaging (MRI) system, we enhance the device sensitivity that results in a substantial improvement of the image quality.

Prostate seed implant quality assessment using MR and CT image fusion.

PubMed

Amdur, R J; Gladstone, D; Leopold, K A; Harris, R D

1999-01-01

After a seed implant of the prostate, computerized tomography (CT) is ideal for determining seed distribution but soft tissue anatomy is frequently not well visualized. Magnetic resonance (MR) images soft tissue anatomy well but seed visualization is problematic. We describe a method of fusing CT and MR images to exploit the advantages of both of these modalities when assessing the quality of a prostate seed implant. Eleven consecutive prostate seed implant patients were imaged with axial MR and CT scans. MR and CT images were fused in three dimensions using the Pinnacle 3.0 version of the ADAC treatment planning system. The urethra and bladder base were used to "line up" MR and CT image sets during image fusion. Alignment was accomplished using translation and rotation in the three ortho-normal planes. Accuracy of image fusion was evaluated by calculating the maximum deviation in millimeters between the center of the urethra on axial MR versus CT images. Implant quality was determined by comparing dosimetric results to previously set parameters. Image fusion was performed with a high degree of accuracy. When lining up the urethra and base of bladder, the maximum difference in axial position of the urethra between MR and CT averaged 2.5 mm (range 1.3-4.0 mm, SD 0.9 mm). By projecting CT-derived dose distributions over MR images of soft tissue structures, qualitative and quantitative evaluation of implant quality is straightforward. The image-fusion process we describe provides a sophisticated way of assessing the quality of a prostate seed implant. Commercial software makes the process time-efficient and available to any clinical practice with a high-quality treatment planning system. While we use MR to image soft tissue structures, the process could be used with any imaging modality that is able to visualize the prostatic urethra (e.g., ultrasound).

TU-AB-207A-03: Image Quality, Dose, and Clinical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, F.

Practicing medical physicists are often time charged with the tasks of evaluating and troubleshooting complex image quality issues related to CT scanners. This course will equip them with a solid and practical understanding of common CT imaging chain and its major components with emphasis on acquisition physics and hardware, reconstruction, artifacts, image quality, dose, and advanced clinical applications. The core objective is to explain the effects of these major system components on the image quality. This course will not focus on the rapid-changing advanced technologies given the two-hour time limit, but the fundamental principles discussed in this course may facilitatemore » better understanding of those more complicated technologies. The course will begin with an overview of CT acquisition physics and geometry. X-ray tube and CT detector are important acquisition hardware critical to the overall image quality. Each of these two subsystems consists of several major components. An in-depth description of the function and failure modes of these components will be provided. Examples of artifacts related to these failure modes will be presented: off-focal radiation, tube arcing, heel effect, oil bubble, offset drift effect, cross-talk effect, and bad pixels. The fundamentals of CT image reconstruction will first be discussed on an intuitive level. Approaches that do not require rigorous derivation of mathematical formulations will be presented. This is followed by a detailed derivation of the Fourier slice theorem: the foundation of the FBP algorithm. FBP for parallel-beam, fan-beam, and cone-beam geometries will be discussed. To address the issue of radiation dose related to x-ray CT, recent advances in iterative reconstruction, their advantages, and clinical applications will also be described. Because of the nature of fundamental physics and mathematics, limitations in data acquisition, and non-ideal conditions of major system components, image artifact

Optimization of image quality and acquisition time for lab-based X-ray microtomography using an iterative reconstruction algorithm

NASA Astrophysics Data System (ADS)

Lin, Qingyang; Andrew, Matthew; Thompson, William; Blunt, Martin J.; Bijeljic, Branko

2018-05-01

Non-invasive laboratory-based X-ray microtomography has been widely applied in many industrial and research disciplines. However, the main barrier to the use of laboratory systems compared to a synchrotron beamline is its much longer image acquisition time (hours per scan compared to seconds to minutes at a synchrotron), which results in limited application for dynamic in situ processes. Therefore, the majority of existing laboratory X-ray microtomography is limited to static imaging; relatively fast imaging (tens of minutes per scan) can only be achieved by sacrificing imaging quality, e.g. reducing exposure time or number of projections. To alleviate this barrier, we introduce an optimized implementation of a well-known iterative reconstruction algorithm that allows users to reconstruct tomographic images with reasonable image quality, but requires lower X-ray signal counts and fewer projections than conventional methods. Quantitative analysis and comparison between the iterative and the conventional filtered back-projection reconstruction algorithm was performed using a sandstone rock sample with and without liquid phases in the pore space. Overall, by implementing the iterative reconstruction algorithm, the required image acquisition time for samples such as this, with sparse object structure, can be reduced by a factor of up to 4 without measurable loss of sharpness or signal to noise ratio.

Improved JPEG anti-forensics with better image visual quality and forensic undetectability.

PubMed

Singh, Gurinder; Singh, Kulbir

2017-08-01

There is an immediate need to validate the authenticity of digital images due to the availability of powerful image processing tools that can easily manipulate the digital image information without leaving any traces. The digital image forensics most often employs the tampering detectors based on JPEG compression. Therefore, to evaluate the competency of the JPEG forensic detectors, an anti-forensic technique is required. In this paper, two improved JPEG anti-forensic techniques are proposed to remove the blocking artifacts left by the JPEG compression in both spatial and DCT domain. In the proposed framework, the grainy noise left by the perceptual histogram smoothing in DCT domain can be reduced significantly by applying the proposed de-noising operation. Two types of denoising algorithms are proposed, one is based on the constrained minimization problem of total variation of energy and other on the normalized weighted function. Subsequently, an improved TV based deblocking operation is proposed to eliminate the blocking artifacts in the spatial domain. Then, a decalibration operation is applied to bring the processed image statistics back to its standard position. The experimental results show that the proposed anti-forensic approaches outperform the existing state-of-the-art techniques in achieving enhanced tradeoff between image visual quality and forensic undetectability, but with high computational cost. Copyright © 2017 Elsevier B.V. All rights reserved.

The medium and the message: a revisionist view of image quality

NASA Astrophysics Data System (ADS)

Ferwerda, James A.

2010-02-01

In his book "Understanding Media" social theorist Marshall McLuhan declared: "The medium is the message." The thesis of this paper is that with respect to image quality, imaging system developers have taken McLuhan's dictum too much to heart. Efforts focus on improving the technical specifications of the media (e.g. dynamic range, color gamut, resolution, temporal response) with little regard for the visual messages the media will be used to communicate. We present a series of psychophysical studies that investigate the visual system's ability to "see through" the limitations of imaging media to perceive the messages (object and scene properties) the images represent. The purpose of these studies is to understand the relationships between the signal characteristics of an image and the fidelity of the visual information the image conveys. The results of these studies provide a new perspective on image quality that shows that images that may be very different in "quality", can be visually equivalent as realistic representations of objects and scenes.

An image quality comparison study between XVI and OBI CBCT systems.

PubMed

Kamath, Srijit; Song, William; Chvetsov, Alexei; Ozawa, Shuichi; Lu, Haibin; Samant, Sanjiv; Liu, Chihray; Li, Jonathan G; Palta, Jatinder R

2011-02-04

The purpose of this study is to evaluate and compare image quality characteristics for two commonly used and commercially available CBCT systems: the X-ray Volumetric Imager and the On-Board Imager. A commonly used CATPHAN image quality phantom was used to measure various image quality parameters, namely, pixel value stability and accuracy, noise, contrast to noise ratio (CNR), high-contrast resolution, low contrast resolution and image uniformity. For the XVI unit, we evaluated the image quality for four manufacturer-supplied protocols as a function of mAs. For the OBI unit, we did the same for the full-fan and half-fan scanning modes, which were respectively used with the full bow-tie and half bow-tie filters. For XVI, the mean pixel values of regions of interest were found to generally decrease with increasing mAs for all protocols, while they were relatively stable with mAs for OBI. Noise was slightly lower on XVI and was seen to decrease with increasing mAs, while CNR increased with mAs for both systems. For XVI and OBI, the high-contrast resolution was approximately limited by the pixel resolution of the reconstructed image. On OBI images, up to 6 and 5 discs of 1% and 0.5% contrast, respectively, were visible for a high mAs setting using the full-fan mode, while none of the discs were clearly visible on the XVI images for various mAs settings when the medium resolution reconstruction was used. In conclusion, image quality parameters for XVI and OBI have been quantified and compared for clinical protocols under various mAs settings. These results need to be viewed in the context of a recent study that reported the dose-mAs relationship for the two systems and found that OBI generally delivered higher imaging doses than XVI.

FFDM image quality assessment using computerized image texture analysis

NASA Astrophysics Data System (ADS)

Berger, Rachelle; Carton, Ann-Katherine; Maidment, Andrew D. A.; Kontos, Despina

2010-04-01

Quantitative measures of image quality (IQ) are routinely obtained during the evaluation of imaging systems. These measures, however, do not necessarily correlate with the IQ of the actual clinical images, which can also be affected by factors such as patient positioning. No quantitative method currently exists to evaluate clinical IQ. Therefore, we investigated the potential of using computerized image texture analysis to quantitatively assess IQ. Our hypothesis is that image texture features can be used to assess IQ as a measure of the image signal-to-noise ratio (SNR). To test feasibility, the "Rachel" anthropomorphic breast phantom (Model 169, Gammex RMI) was imaged with a Senographe 2000D FFDM system (GE Healthcare) using 220 unique exposure settings (target/filter, kVs, and mAs combinations). The mAs were varied from 10%-300% of that required for an average glandular dose (AGD) of 1.8 mGy. A 2.5cm2 retroareolar region of interest (ROI) was segmented from each image. The SNR was computed from the ROIs segmented from images linear with dose (i.e., raw images) after flat-field and off-set correction. Image texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the Premium ViewTM postprocessed image ROIs. Multiple linear regression demonstrated a strong association between the computed image texture features and SNR (R2=0.92, p<=0.001). When including kV, target and filter as additional predictor variables, a stronger association with SNR was observed (R2=0.95, p<=0.001). The strong associations indicate that computerized image texture analysis can be used to measure image SNR and potentially aid in automating IQ assessment as a component of the clinical workflow. Further work is underway to validate our findings in larger clinical datasets.

Image reconstructions from super-sampled data sets with resolution modeling in PET imaging.

PubMed

Li, Yusheng; Matej, Samuel; Metzler, Scott D

2014-12-01

Spatial resolution in positron emission tomography (PET) is still a limiting factor in many imaging applications. To improve the spatial resolution for an existing scanner with fixed crystal sizes, mechanical movements such as scanner wobbling and object shifting have been considered for PET systems. Multiple acquisitions from different positions can provide complementary information and increased spatial sampling. The objective of this paper is to explore an efficient and useful reconstruction framework to reconstruct super-resolution images from super-sampled low-resolution data sets. The authors introduce a super-sampling data acquisition model based on the physical processes with tomographic, downsampling, and shifting matrices as its building blocks. Based on the model, we extend the MLEM and Landweber algorithms to reconstruct images from super-sampled data sets. The authors also derive a backprojection-filtration-like (BPF-like) method for the super-sampling reconstruction. Furthermore, they explore variant methods for super-sampling reconstructions: the separate super-sampling resolution-modeling reconstruction and the reconstruction without downsampling to further improve image quality at the cost of more computation. The authors use simulated reconstruction of a resolution phantom to evaluate the three types of algorithms with different super-samplings at different count levels. Contrast recovery coefficient (CRC) versus background variability, as an image-quality metric, is calculated at each iteration for all reconstructions. The authors observe that all three algorithms can significantly and consistently achieve increased CRCs at fixed background variability and reduce background artifacts with super-sampled data sets at the same count levels. For the same super-sampled data sets, the MLEM method achieves better image quality than the Landweber method, which in turn achieves better image quality than the BPF-like method. The authors also demonstrate

CLINICAL AUDIT OF IMAGE QUALITY IN RADIOLOGY USING VISUAL GRADING CHARACTERISTICS ANALYSIS.

PubMed

Tesselaar, Erik; Dahlström, Nils; Sandborg, Michael

2016-06-01

The aim of this work was to assess whether an audit of clinical image quality could be efficiently implemented within a limited time frame using visual grading characteristics (VGC) analysis. Lumbar spine radiography, bedside chest radiography and abdominal CT were selected. For each examination, images were acquired or reconstructed in two ways. Twenty images per examination were assessed by 40 radiology residents using visual grading of image criteria. The results were analysed using VGC. Inter-observer reliability was assessed. The results of the visual grading analysis were consistent with expected outcomes. The inter-observer reliability was moderate to good and correlated with perceived image quality (r(2) = 0.47). The median observation time per image or image series was within 2 min. These results suggest that the use of visual grading of image criteria to assess the quality of radiographs provides a rapid method for performing an image quality audit in a clinical environment. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Image quality assessment of silent T2 PROPELLER sequence for brain imaging in infants.

PubMed

Kim, Hyun Gi; Choi, Jin Wook; Yoon, Soo Han; Lee, Sieun

2018-02-01

Infants are vulnerable to high acoustic noise. Acoustic noise generated by MR scanning can be reduced by a silent sequence. The purpose of this study is to compare the image quality of the conventional and silent T2 PROPELLER sequences for brain imaging in infants. A total of 36 scans were acquired from 24 infants using a 3 T MR scanner. Each patient underwent both conventional and silent T2 PROPELLER sequences. Acoustic noise level was measured. Quantitative and qualitative assessments were performed with the images taken with each sequence. The sound pressure level of the conventional T2 PROPELLER imaging sequence was 92.1 dB and that of the silent T2 PROPELLER imaging sequence was 73.3 dB (reduction of 20%). On quantitative assessment, the two sequences (conventional vs silent T2 PROPELLER) did not show significant difference in relative contrast (0.069 vs 0.068, p value = 0.536) and signal-to-noise ratio (75.4 vs 114.8, p value = 0.098). Qualitative assessment of overall image quality (p value = 0.572), grey-white differentiation (p value = 0.986), shunt-related artefact (p value > 0.999), motion artefact (p value = 0.801) and myelination degree in different brain regions (p values ≥ 0.092) did not show significant difference between the two sequences. The silent T2 PROPELLER sequence reduces acoustic noise and generated comparable image quality to that of the conventional sequence. Advances in knowledge: This is the first report to compare silent T2 PROPELLER images with that of conventional T2 PROPELLER images in children.

SU-E-J-36: Comparison of CBCT Image Quality for Manufacturer Default Imaging Modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, G

Purpose CBCT is being increasingly used in patient setup for radiotherapy. Often the manufacturer default scan modes are used for performing these CBCT scans with the assumption that they are the best options. To quantitatively assess the image quality of these scan modes, all of the scan modes were tested as well as options with the reconstruction algorithm. Methods A CatPhan 504 phantom was scanned on a TrueBeam Linear Accelerator using the manufacturer scan modes (FSRT Head, Head, Image Gently, Pelvis, Pelvis Obese, Spotlight, & Thorax). The Head mode scan was then reconstructed multiple times with all filter options (Smooth,more » Standard, Sharp, & Ultra Sharp) and all Ring Suppression options (Disabled, Weak, Medium, & Strong). An open source ImageJ tool was created for analyzing the CatPhan 504 images. Results The MTF curve was primarily dictated by the voxel size and the filter used in the reconstruction algorithm. The filters also impact the image noise. The CNR was worst for the Image Gently mode, followed by FSRT Head and Head. The sharper the filter, the worse the CNR. HU varied significantly between scan modes. Pelvis Obese had lower than expected HU values than most while the Image Gently mode had higher than expected HU values. If a therapist tried to use preset window and level settings, they would not show the desired tissue for some scan modes. Conclusion Knowing the image quality of the set scan modes, will enable users to better optimize their setup CBCT. Evaluation of the scan mode image quality could improve setup efficiency and lead to better treatment outcomes.« less

Evaluation of image quality in terahertz pulsed imaging using test objects.

PubMed

Fitzgerald, A J; Berry, E; Miles, R E; Zinovev, N N; Smith, M A; Chamberlain, J M

2002-11-07

As with other imaging modalities, the performance of terahertz (THz) imaging systems is limited by factors of spatial resolution, contrast and noise. The purpose of this paper is to introduce test objects and image analysis methods to evaluate and compare THz image quality in a quantitative and objective way, so that alternative terahertz imaging system configurations and acquisition techniques can be compared, and the range of image parameters can be assessed. Two test objects were designed and manufactured, one to determine the modulation transfer functions (MTF) and the other to derive image signal to noise ratio (SNR) at a range of contrasts. As expected the higher THz frequencies had larger MTFs, and better spatial resolution as determined by the spatial frequency at which the MTF dropped below the 20% threshold. Image SNR was compared for time domain and frequency domain image parameters and time delay based images consistently demonstrated higher SNR than intensity based parameters such as relative transmittance because the latter are more strongly affected by the sources of noise in the THz system such as laser fluctuations and detector shot noise.

Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data.

PubMed

Gu, Ke; Tao, Dacheng; Qiao, Jun-Fei; Lin, Weisi

2018-04-01

In this paper, we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g., object detection and recognition, raw images are usually needed to be appropriately enhanced to raise the visual quality (e.g., visibility and contrast). In fact, proper enhancement can noticeably improve the quality of input images, even better than originally captured images, which are generally thought to be of the best quality. In this paper, we present two most important contributions. The first contribution is to develop a new no-reference (NR) IQA model. Given an image, our quality measure first extracts 17 features through analysis of contrast, sharpness, brightness and more, and then yields a measure of visual quality using a regression module, which is learned with big-data training samples that are much bigger than the size of relevant image data sets. The results of experiments on nine data sets validate the superiority and efficiency of our blind metric compared with typical state-of-the-art full-reference, reduced-reference and NA IQA methods. The second contribution is that a robust image enhancement framework is established based on quality optimization. For an input image, by the guidance of the proposed NR-IQA measure, we conduct histogram modification to successively rectify image brightness and contrast to a proper level. Thorough tests demonstrate that our framework can well enhance natural images, low-contrast images, low-light images, and dehazed images. The source code will be released at https://sites.google.com/site/guke198701/publications.

Assessing the quality of restored images in optical long-baseline interferometry

NASA Astrophysics Data System (ADS)

Gomes, Nuno; Garcia, Paulo J. V.; Thiébaut, Éric

2017-03-01

Assessing the quality of aperture synthesis maps is relevant for benchmarking image reconstruction algorithms, for the scientific exploitation of data from optical long-baseline interferometers, and for the design/upgrade of new/existing interferometric imaging facilities. Although metrics have been proposed in these contexts, no systematic study has been conducted on the selection of a robust metric for quality assessment. This article addresses the question: what is the best metric to assess the quality of a reconstructed image? It starts by considering several metrics and selecting a few based on general properties. Then, a variety of image reconstruction cases are considered. The observational scenarios are phase closure and phase referencing at the Very Large Telescope Interferometer (VLTI), for a combination of two, three, four and six telescopes. End-to-end image reconstruction is accomplished with the MIRA software, and several merit functions are put to test. It is found that convolution by an effective point spread function is required for proper image quality assessment. The effective angular resolution of the images is superior to naive expectation based on the maximum frequency sampled by the array. This is due to the prior information used in the aperture synthesis algorithm and to the nature of the objects considered. The ℓ1-norm is the most robust of all considered metrics, because being linear it is less sensitive to image smoothing by high regularization levels. For the cases considered, this metric allows the implementation of automatic quality assessment of reconstructed images, with a performance similar to human selection.

Translation position determination in ptychographic coherent diffraction imaging.

PubMed

Zhang, Fucai; Peterson, Isaac; Vila-Comamala, Joan; Diaz, Ana; Berenguer, Felisa; Bean, Richard; Chen, Bo; Menzel, Andreas; Robinson, Ian K; Rodenburg, John M

2013-06-03

Accurate knowledge of translation positions is essential in ptychography to achieve a good image quality and the diffraction limited resolution. We propose a method to retrieve and correct position errors during the image reconstruction iterations. Sub-pixel position accuracy after refinement is shown to be achievable within several tens of iterations. Simulation and experimental results for both optical and X-ray wavelengths are given. The method improves both the quality of the retrieved object image and relaxes the position accuracy requirement while acquiring the diffraction patterns.

Optimisation of radiation dose and image quality in mobile neonatal chest radiography.

PubMed

Hinojos-Armendáriz, V I; Mejía-Rosales, S J; Franco-Cabrera, M C

2018-05-01

To optimise the radiation dose and image quality for chest radiography in the neonatal intensive care unit (NICU) by increasing the mean beam energy. Two techniques for the acquisition of NICU AP chest X-ray images were compared for image quality and radiation dose. 73 images were acquired using a standard technique (56 kV, 3.2 mAs and no additional filtration) and 90 images with a new technique (62 kV, 2 mAs and 2 mm Al filtration). The entrance surface air kerma (ESAK) was measured using a phantom and compared between the techniques and against established diagnostic reference levels (DRL). Images were evaluated using seven image quality criteria independently by three radiologists. Images quality and radiation dose were compared statistically between the standard and new techniques. The maximum ESAK for the new technique was 40.20 μGy, 43.7% of the ESAK of the standard technique. Statistical evaluation demonstrated no significant differences in image quality between the two acquisition techniques. Based on the techniques and acquisition factors investigated within this study, it is possible to lower the radiation dose without any significant effects on image quality by adding filtration (2 mm Al) and increasing the tube potential. Such steps are relatively simple to undertake and as such, other departments should consider testing and implementing this dose reduction strategy within clinical practice where appropriate. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Lung nodule detection in pediatric chest CT: quantitative relationship between image quality and radiologist performance.

PubMed

Li, Xiang; Samei, Ehsan; Barnhart, Huiman X; Gaca, Ana Maria; Hollingsworth, Caroline L; Maxfield, Charles M; Carrico, Caroline W T; Colsher, James G; Frush, Donald P

2011-05-01

To determine the quantitative relationship between image quality and radiologist performance in detecting small lung nodules in pediatric CT. The study included clinical chest CT images of 30 pediatric patients (0-16 years) scanned at tube currents of 55-180 mA. Calibrated noise addition software was used to simulate cases at three nominal mA settings: 70, 35, and 17.5 mA, resulting in quantum noise of 7-32 Hounsfield Unit (HU). Using a validated nodule simulation technique, lung nodules with diameters of 3-5 mm and peak contrasts of 200-500 HU were inserted into the cases, which were then randomized and rated independently by four experienced pediatric radiologists for nodule presence on a continuous scale from 0 (definitely absent) to 100 (definitely present). The receiver operating characteristic (ROC) data were analyzed to quantify the relationship between diagnostic accuracy (area under the ROC curve, AUC) and image quality (the product of nodule peak contrast and displayed diameter to noise ratio, CDNR display). AUC increased rapidly from 0.70 to 0.87 when CDNR display increased from 60 to 130 mm, followed by a slow increase to 0.94 when CDNR display further increased to 257 mm. For the average nodule diameter (4 mm) and contrast (350 HU), AUC decreased from 0.93 to 0.71 with noise increased from 7 to 28 HU. We quantified the relationship between image quality and the performance of radiologists in detecting lung nodules in pediatric CT. The relationship can guide CT protocol design to achieve the desired diagnostic performance at the lowest radiation dose.

Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

PubMed

Mori, Shinichiro

2017-08-01

To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

New patient-controlled abdominal compression method in radiography: radiation dose and image quality.

PubMed

Piippo-Huotari, Oili; Norrman, Eva; Anderzén-Carlsson, Agneta; Geijer, Håkan

2018-05-01

The radiation dose for patients can be reduced with many methods and one way is to use abdominal compression. In this study, the radiation dose and image quality for a new patient-controlled compression device were compared with conventional compression and compression in the prone position . To compare radiation dose and image quality of patient-controlled compression compared with conventional and prone compression in general radiography. An experimental design with quantitative approach. After obtaining the approval of the ethics committee, a consecutive sample of 48 patients was examined with the standard clinical urography protocol. The radiation doses were measured as dose-area product and analyzed with a paired t-test. The image quality was evaluated by visual grading analysis. Four radiologists evaluated each image individually by scoring nine criteria modified from the European quality criteria for diagnostic radiographic images. There was no significant difference in radiation dose or image quality between conventional and patient-controlled compression. Prone position resulted in both higher dose and inferior image quality. Patient-controlled compression gave similar dose levels as conventional compression and lower than prone compression. Image quality was similar with both patient-controlled and conventional compression and was judged to be better than in the prone position.

Image quality and stability of image-guided radiotherapy (IGRT) devices: A comparative study

PubMed Central

Stock, Markus; Pasler, Marlies; Birkfellner, Wolfgang; Homolka, Peter; Poetter, Richard; Georg, Dietmar

2010-01-01

Introduction Our aim was to implement standards for quality assurance of IGRT devices used in our department and to compare their performances with that of a CT simulator. Materials and methods We investigated image quality parameters for three devices over a period of 16 months. A multislice CT was used as a benchmark and results related to noise, spatial resolution, low contrast visibility (LCV) and uniformity were compared with a cone beam CT (CBCT) at a linac and simulator. Results All devices performed well in terms of LCV and, in fact, exceeded vendor specifications. MTF was comparable between CT and linac CBCT. Integral nonuniformity was, on average, 0.002 for the CT and 0.006 for the linac CBCT. Uniformity, LCV and MTF varied depending on the protocols used for the linac CBCT. Contrast-to-noise ratio was an average of 51% higher for the CT than for the linac and simulator CBCT. No significant time trend was observed and tolerance limits were implemented. Discussion Reasonable differences in image quality between CT and CBCT were observed. Further research and development are necessary to increase image quality of commercially available CBCT devices in order for them to serve the needs for adaptive and/or online planning. PMID:19695725

Blind image quality assessment via probabilistic latent semantic analysis.

PubMed

Yang, Xichen; Sun, Quansen; Wang, Tianshu

2016-01-01

We propose a blind image quality assessment that is highly unsupervised and training free. The new method is based on the hypothesis that the effect caused by distortion can be expressed by certain latent characteristics. Combined with probabilistic latent semantic analysis, the latent characteristics can be discovered by applying a topic model over a visual word dictionary. Four distortion-affected features are extracted to form the visual words in the dictionary: (1) the block-based local histogram; (2) the block-based local mean value; (3) the mean value of contrast within a block; (4) the variance of contrast within a block. Based on the dictionary, the latent topics in the images can be discovered. The discrepancy between the frequency of the topics in an unfamiliar image and a large number of pristine images is applied to measure the image quality. Experimental results for four open databases show that the newly proposed method correlates well with human subjective judgments of diversely distorted images.

Effect of injection rate on contrast-enhanced MR angiography image quality: Modulation transfer function analysis.

PubMed

Clark, Toshimasa J; Wilson, Gregory J; Maki, Jeffrey H

2017-07-01

Contrast-enhanced (CE)-MRA optimization involves interactions of sequence duration, bolus timing, contrast recirculation, and both R 1 relaxivity and R2*-related reduction of signal. Prior data suggest superior image quality with slower gadolinium injection rates than typically used. A computer-based model of CE-MRA was developed, with contrast injection, physiologic, and image acquisition parameters varied over a wide gamut. Gadolinium concentration was derived using Verhoeven's model with recirculation, R 1 and R2* calculated at each time point, and modulation transfer curves used to determine injection rates, resulting in optimal resolution and image contrast for renal and carotid artery CE-MRA. Validation was via a vessel stenosis phantom and example patients who underwent carotid CE-MRA with low effective injection rates. Optimal resolution for renal and carotid CE-MRA is achieved with injection rates between 0.5 to 0.9 mL/s and 0.2 to 0.3 mL/s, respectively, dependent on contrast volume. Optimal image contrast requires slightly faster injection rates. Expected signal-to-noise ratio varies with both contrast volume and cardiac output. Simulated vessel phantom and clinical carotid CE-MRA exams at an effective contrast injection rate of 0.4 to 0.5 mL/s demonstrate increased resolution. Optimal image resolution is achieved at intuitively low, effective injection rates (0.2-0.9 mL/s, dependent on imaging parameters and contrast injection volume). Magn Reson Med 78:357-369, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Functional magnetic resonance imaging of awake monkeys: some approaches for improving imaging quality

PubMed Central

Chen, Gang; Wang, Feng; Dillenburger, Barbara C.; Friedman, Robert M.; Chen, Li M.; Gore, John C.; Avison, Malcolm J.; Roe, Anna W.

2011-01-01

Functional magnetic resonance imaging (fMRI), at high magnetic field strength can suffer from serious degradation of image quality because of motion and physiological noise, as well as spatial distortions and signal losses due to susceptibility effects. Overcoming such limitations is essential for sensitive detection and reliable interpretation of fMRI data. These issues are particularly problematic in studies of awake animals. As part of our initial efforts to study functional brain activations in awake, behaving monkeys using fMRI at 4.7T, we have developed acquisition and analysis procedures to improve image quality with encouraging results. We evaluated the influence of two main variables on image quality. First, we show how important the level of behavioral training is for obtaining good data stability and high temporal signal-to-noise ratios. In initial sessions, our typical scan session lasted 1.5 hours, partitioned into short (<10 minutes) runs. During reward periods and breaks between runs, the monkey exhibited movements resulting in considerable image misregistrations. After a few months of extensive behavioral training, we were able to increase the length of individual runs and the total length of each session. The monkey learned to wait until the end of a block for fluid reward, resulting in longer periods of continuous acquisition. Each additional 60 training sessions extended the duration of each session by 60 minutes, culminating, after about 140 training sessions, in sessions that last about four hours. As a result, the average translational movement decreased from over 500 μm to less than 80 μm, a displacement close to that observed in anesthetized monkeys scanned in a 7 T horizontal scanner. Another major source of distortion at high fields arises from susceptibility variations. To reduce such artifacts, we used segmented gradient-echo echo-planar imaging (EPI) sequences. Increasing the number of segments significantly decreased susceptibility

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Application-Driven No-Reference Quality Assessment for Dermoscopy Images With Multiple Distortions.

PubMed

Xie, Fengying; Lu, Yanan; Bovik, Alan C; Jiang, Zhiguo; Meng, Rusong

2016-06-01

Dermoscopy images often suffer from blur and uneven illumination distortions that occur during acquisition, which can adversely influence consequent automatic image analysis results on potential lesion objects. The purpose of this paper is to deploy an algorithm that can automatically assess the quality of dermoscopy images. Such an algorithm could be used to direct image recapture or correction. We describe an application-driven no-reference image quality assessment (IQA) model for dermoscopy images affected by possibly multiple distortions. For this purpose, we created a multiple distortion dataset of dermoscopy images impaired by varying degrees of blur and uneven illumination. The basis of this model is two single distortion IQA metrics that are sensitive to blur and uneven illumination, respectively. The outputs of these two metrics are combined to predict the quality of multiply distorted dermoscopy images using a fuzzy neural network. Unlike traditional IQA algorithms, which use human subjective score as ground truth, here ground truth is driven by the application, and generated according to the degree of influence of the distortions on lesion analysis. The experimental results reveal that the proposed model delivers accurate and stable quality prediction results for dermoscopy images impaired by multiple distortions. The proposed model is effective for quality assessment of multiple distorted dermoscopy images. An application-driven concept for IQA is introduced, and at the same time, a solution framework for the IQA of multiple distortions is proposed.

Image Acquisition and Quality in Digital Radiography.

PubMed

Alexander, Shannon

2016-09-01

Medical imaging has undergone dramatic changes and technological breakthroughs since the introduction of digital radiography. This article presents information on the development of digital radiography and types of digital radiography systems. Aspects of image quality and radiation exposure control are highlighted as well. In addition, the article includes related workplace changes and medicolegal considerations in the digital radiography environment. ©2016 American Society of Radiologic Technologists.

WE-G-207-05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, J; Nishikawa, R; Reiser, I

Purpose: Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis. Methods: A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benignmore » or malignant. Twenty-three image features were extracted after segmentation using a semi-automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave-one-out-cross-validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist’s drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared. Results: Moderate correlation (Pearson’s rho = 0.43, p-value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance. Conclusion: There are certain images that yield better segmentation or

Super-resolution convolutional neural network for the improvement of the image quality of magnified images in chest radiographs

NASA Astrophysics Data System (ADS)

Umehara, Kensuke; Ota, Junko; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

2017-02-01

Single image super-resolution (SR) method can generate a high-resolution (HR) image from a low-resolution (LR) image by enhancing image resolution. In medical imaging, HR images are expected to have a potential to provide a more accurate diagnosis with the practical application of HR displays. In recent years, the super-resolution convolutional neural network (SRCNN), which is one of the state-of-the-art deep learning based SR methods, has proposed in computer vision. In this study, we applied and evaluated the SRCNN scheme to improve the image quality of magnified images in chest radiographs. For evaluation, a total of 247 chest X-rays were sampled from the JSRT database. The 247 chest X-rays were divided into 93 training cases with non-nodules and 152 test cases with lung nodules. The SRCNN was trained using the training dataset. With the trained SRCNN, the HR image was reconstructed from the LR one. We compared the image quality of the SRCNN and conventional image interpolation methods, nearest neighbor, bilinear and bicubic interpolations. For quantitative evaluation, we measured two image quality metrics, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the SRCNN scheme, PSNR and SSIM were significantly higher than those of three interpolation methods (p<0.001). Visual assessment confirmed that the SRCNN produced much sharper edge than conventional interpolation methods without any obvious artifacts. These preliminary results indicate that the SRCNN scheme significantly outperforms conventional interpolation algorithms for enhancing image resolution and that the use of the SRCNN can yield substantial improvement of the image quality of magnified images in chest radiographs.

Whole-surface round object imaging method using line-scan hyperspectral imaging system

USDA-ARS?s Scientific Manuscript database

To achieve comprehensive online quality and safety inspection of fruits, whole-surface sample presentation and imaging regimes must be considered. Specifically, a round object sample presentation method is under development to achieve effective whole-surface sample evaluation based on the use of a s...

Body Image, Self-esteem, and Quality of Life in Patients with Psoriasis.

PubMed

Nazik, Hulya; Nazik, Selcuk; Gul, Feride C

2017-01-01

Psoriasis is a chronic inflammatory disease of the skin that may affect the visible areas of body. Hence, the quality of life, self-esteem, and body image can be affected in psoriasis patients. We aimed in the present study to assess the effects of psoriasis on the quality of life, self-esteem, and body image. The study included 92 patients with psoriasis, along with 98 control participants. The sociodemographic characteristics of the patients were assessed, their Psoriasis Area Severity Index (PASI) scores were calculated to determine the clinical severity of the psoriasis, and the values were recorded. In addition, Dermatology Life Quality Index (DLQI), Body Image Scale, and Rosenberg Self-Esteem Scale results were evaluated. When the control and psoriasis groups were evaluated regarding the DLQI, self-esteem, and body image, quality of life was found to be more negatively affected in the psoriasis group than the controls, which was statistically significant ( P < 0.001), and self-esteem ( P < 0.001) and body image ( P < 0.001) were found to be significantly lower. Educational status significantly affected self-esteem ( P < 0.001) and body image ( P = 0.021), however, quality of life was not significantly affected by this parameter ( P = 0.345). PASI was positively correlated with the quality of life ( r = 0.703) and self-esteem ( r = 0.448), however, it was negatively correlated with the body image ( r = -0.423). Psoriasis may negatively affect quality of life, self-esteem, and body image, and may also cause psychosocial problems. An assessment of new approaches on this issue may contribute to developments in the treatment of and rehabilitation from this disease.

Evaluation of image quality of digital photo documentation of female genital injuries following sexual assault.

PubMed

Ernst, E J; Speck, Patricia M; Fitzpatrick, Joyce J

2011-12-01

With the patient's consent, physical injuries sustained in a sexual assault are evaluated and treated by the sexual assault nurse examiner (SANE) and documented on preprinted traumagrams and with photographs. Digital imaging is now available to the SANE for documentation of sexual assault injuries, but studies of the image quality of forensic digital imaging of female genital injuries after sexual assault were not found in the literature. The Photo Documentation Image Quality Scoring System (PDIQSS) was developed to rate the image quality of digital photo documentation of female genital injuries after sexual assault. Three expert observers performed evaluations on 30 separate images at two points in time. An image quality score, the sum of eight integral technical and anatomical attributes on the PDIQSS, was obtained for each image. Individual image quality ratings, defined by rating image quality for each of the data, were also determined. The results demonstrated a high level of image quality and agreement when measured in all dimensions. For the SANE in clinical practice, the results of this study indicate that a high degree of agreement exists between expert observers when using the PDIQSS to rate image quality of individual digital photographs of female genital injuries after sexual assault. © 2011 International Association of Forensic Nurses.

Quality Education in Idaho: A Case Study of Academic Achievement in Three High-Poverty Rural Schools

ERIC Educational Resources Information Center

Brown, Christine

2017-01-01

The focus of this research is bridging the achievement gap for students living in poverty through quality education. Such a study is important because the percentage of students affected by poverty is increasing and the persistent gap in achievement evidences that the right to quality education for students in poverty is not being met. This is…

Image quality stability of whole-body diffusion weighted imaging.

PubMed

Chen, Yun-bin; Hu, Chun-miao; Zhong, Jing; Sun, Fei

2009-06-01

To assess the reproducibility of whole-body diffusion weighted imaging (WB-DWI) technique in healthy volunteers under normal breathing with background body signal suppression. WB-DWI was performed on 32 healthy volunteers twice within two-week period using short TI inversion-recovery diffusion-weighted echo-planar imaging sequence and built-in body coil. The volunteers were scanned across six stations continuously covering the entire body from the head to the feet under normal breathing. The bone apparent diffusion coefficient (ADC) and exponential ADC (eADC) of regions of interest (ROIs) were measured. We analyzed correlation of the results using paired-t-test to assess the reproducibility of the WB-DWI technique. We were successful in collecting and analyzing data of 64 WB-DWI images. There was no significant difference in bone ADC and eADC of 824 ROIs between the paired observers and paired scans (P>0.05). Most of the images from all stations were of diagnostic quality. The measurements of bone ADC and eADC have good reproducibility. WB-DWI technique under normal breathing with background body signal suppression is adequate.

The influence of software filtering in digital mammography image quality

NASA Astrophysics Data System (ADS)

Michail, C.; Spyropoulou, V.; Kalyvas, N.; Valais, I.; Dimitropoulos, N.; Fountos, G.; Kandarakis, I.; Panayiotakis, G.

2009-05-01

Breast cancer is one of the most frequently diagnosed cancers among women. Several techniques have been developed to help in the early detection of breast cancer such as conventional and digital x-ray mammography, positron and single-photon emission mammography, etc. A key advantage in digital mammography is that images can be manipulated as simple computer image files. Thus non-dedicated commercially available image manipulation software can be employed to process and store the images. The image processing tools of the Photoshop (CS 2) software usually incorporate digital filters which may be used to reduce image noise, enhance contrast and increase spatial resolution. However, improving an image quality parameter may result in degradation of another. The aim of this work was to investigate the influence of three sharpening filters, named hereafter sharpen, sharpen more and sharpen edges on image resolution and noise. Image resolution was assessed by means of the Modulation Transfer Function (MTF).In conclusion it was found that the correct use of commercial non-dedicated software on digital mammograms may improve some aspects of image quality.

Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images

PubMed Central

Osadebey, Michael; Pedersen, Marius; Arnold, Douglas; Wendel-Mitoraj, Katrina

2017-01-01

Abstract. We describe a postacquisition, attribute-based quality assessment method for brain magnetic resonance imaging (MRI) images. It is based on the application of Bayes theory to the relationship between entropy and image quality attributes. The entropy feature image of a slice is segmented into low- and high-entropy regions. For each entropy region, there are three separate observations of contrast, standard deviation, and sharpness quality attributes. A quality index for a quality attribute is the posterior probability of an entropy region given any corresponding region in a feature image where quality attribute is observed. Prior belief in each entropy region is determined from normalized total clique potential (TCP) energy of the slice. For TCP below the predefined threshold, the prior probability for a region is determined by deviation of its percentage composition in the slice from a standard normal distribution built from 250 MRI volume data provided by Alzheimer’s Disease Neuroimaging Initiative. For TCP above the threshold, the prior is computed using a mathematical model that describes the TCP–noise level relationship in brain MRI images. Our proposed method assesses the image quality of each entropy region and the global image. Experimental results demonstrate good correlation with subjective opinions of radiologists for different types and levels of quality distortions. PMID:28630885

“Lucky Averaging”: Quality improvement on Adaptive Optics Scanning Laser Ophthalmoscope Images

PubMed Central

Huang, Gang; Zhong, Zhangyi; Zou, Weiyao; Burns, Stephen A.

2012-01-01

Adaptive optics(AO) has greatly improved retinal image resolution. However, even with AO, temporal and spatial variations in image quality still occur due to wavefront fluctuations, intra-frame focus shifts and other factors. As a result, aligning and averaging images can produce a mean image that has lower resolution or contrast than the best images within a sequence. To address this, we propose an image post-processing scheme called “lucky averaging”, analogous to lucky imaging (Fried, 1978) based on computing the best local contrast over time. Results from eye data demonstrate improvements in image quality. PMID:21964097

Impact of Adaptive Statistical Iterative Reconstruction (ASIR) on radiation dose and image quality in aortic dissection studies: a qualitative and quantitative analysis.

PubMed

Cornfeld, Daniel; Israel, Gary; Detroy, Ezra; Bokhari, Jamal; Mojibian, Hamid

2011-03-01

The purpose of the study was to quantify the radiation dose reduction achieved when imaging the aorta using Adaptive Statistical Iterative Reconstruction (ASIR) and to determine if this has an effect on image quality. We retrospectively reviewed 31 CT angiography examinations of the thoracic and abdominal aorta performed with ASIR and 32 consecutive similar examinations performed without ASIR. Volume CT dose index (CTDI(vol)), dose-length product (DLP), aortic enhancement at multiple levels, aorta-to-muscle contrast-to-noise ratio at multiple levels, and subjective image quality were compared between the two groups. The mean CTDI(vol) and DLP were significantly lower for the studies performed with ASIR versus studies without ASIR (15.6 vs 21.5 mGy, with an average difference of 5.8 mGy [95% CI 2.3-9.4 mGy] and 818 vs 1075 mGy × cm with an average difference of -257 mGy × cm [54-460 mGy × cm], respectively). Aortic enhancement, aortic signal-to-noise ratio, and aortic to muscle contrast-to-noise ratio were not different between the two groups. Subjectively, one reviewer preferred the non-ASIR images and one found the images equivalent. Both reviewers believed the images were of diagnostic quality. A 29% decrease in CTDI(vol) and a 20% decrease in DLP were obtained in scans with ASIR compared with scans without ASIR, without a quantitative loss of image quality.

An inter-laboratory comparison study of image quality of PET scanners using the NEMA NU 2-2001 procedure for assessment of image quality

NASA Astrophysics Data System (ADS)

Bergmann, Helmar; Dobrozemsky, Georg; Minear, Gregory; Nicoletti, Rudolf; Samal, Martin

2005-05-01

An inter-laboratory comparison study was conducted to assess the image quality of PET scanners in Austria. The survey included both dedicated PET scanners (D-PET, n = 8) and coincidence cameras (GC-PET, n = 7). Measurement of image quality was based on the NEMA (National Electrical Manufacturers Association) NU 2-2001 protocol and the IEC (International Electrotechnical Commission) body phantom. The latter contains six fillable spheres ranging in diameter from 37 mm down to 10 mm and a 'lung' insert. The two largest lesions L1-2 simulate cold lesions, the four smaller ones (L3-6) are filled with 18F and activity concentration ratios relative to background of 8:1 and 4:1, respectively. Acquisition and reconstruction in the study employed the participating institutes' standard oncological processing protocol. Calculation of contrast of the spheres was performed with a fully automated procedure. Contrast quality indices (CQIs) reflecting global performance were obtained by summing individual contrast values. Other image quality parameters calculated according to the NEMA protocol were background variability and relative error for correction of attenuation and scatter. Contrast values obtained were 61 ± 16 and 37 ± 14 for L1 (per cent contrast ± SD for D-PET and GC-PET, respectively), 57 ± 16 and 29 ± 16 for L2, 46 ± 10 and 26 ± 6.3 for L3, 37 ± 10 and 15 ± 4.3 for L4, 26 ± 11.5 and 6.1 ± 2.5 for L5, 14 ± 7.1 and 2.6 ± 2.6 for L6, with D-PET systems consistently being superior to GC-PET systems. CQIs permitted ranking of the scanners, also demonstrating a clear distinction between D-PET and GC-PET systems. Background variability was largest for GC-PET systems; the relative error of attenuation and scatter correction was significantly correlated with image quality for D-PET systems only. The study demonstrated considerable differences in image quality not only between GC-PET and D-PET systems but also between individual D-PET systems with possible

Relationships among muscle dysmorphia characteristics, body image quality of life, and coping in males.

PubMed

Tod, D; Edwards, C

2015-09-01

The purpose of this study was to examine relationships among bodybuilding dependence, muscle satisfaction, body image-related quality of life and body image-related coping strategies, and test the hypothesis that muscle dysmorphia characteristics may predict quality of life via coping strategies. Participants (294 males, Mage=20.5 years, SD=3.1) participated in a cross-sectional survey. Participants completed questionnaires assessing muscle satisfaction, bodybuilding dependence, body image-related quality of life and body image-related coping. Quality of life was correlated positively with muscle satisfaction and bodybuilding dependence but negatively with body image coping (P<0.05). Body image coping was correlated positively with bodybuilding dependence and negatively with muscle satisfaction (P<0.05). Mediation analysis found that bodybuilding dependence and muscle satisfaction predicted quality of life both directly and indirectly via body image coping strategies (as evidenced by the bias corrected and accelerated bootstrapped confidence intervals). These results provide preliminary evidence regarding the ways that muscularity concerns might influence body image-related quality of life. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Simultaneous fluoroscopic and nuclear imaging: impact of collimator choice on nuclear image quality.

PubMed

van der Velden, Sandra; Beijst, Casper; Viergever, Max A; de Jong, Hugo W A M

2017-01-01

X-ray-guided oncological interventions could benefit from the availability of simultaneously acquired nuclear images during the procedure. To this end, a real-time, hybrid fluoroscopic and nuclear imaging device, consisting of an X-ray c-arm combined with gamma imaging capability, is currently being developed (Beijst C, Elschot M, Viergever MA, de Jong HW. Radiol. 2015;278:232-238). The setup comprises four gamma cameras placed adjacent to the X-ray tube. The four camera views are used to reconstruct an intermediate three-dimensional image, which is subsequently converted to a virtual nuclear projection image that overlaps with the X-ray image. The purpose of the present simulation study is to evaluate the impact of gamma camera collimator choice (parallel hole versus pinhole) on the quality of the virtual nuclear image. Simulation studies were performed with a digital image quality phantom including realistic noise and resolution effects, with a dynamic frame acquisition time of 1 s and a total activity of 150 MBq. Projections were simulated for 3, 5, and 7 mm pinholes and for three parallel hole collimators (low-energy all-purpose (LEAP), low-energy high-resolution (LEHR) and low-energy ultra-high-resolution (LEUHR)). Intermediate reconstruction was performed with maximum likelihood expectation-maximization (MLEM) with point spread function (PSF) modeling. In the virtual projection derived therefrom, contrast, noise level, and detectability were determined and compared with the ideal projection, that is, as if a gamma camera were located at the position of the X-ray detector. Furthermore, image deformations and spatial resolution were quantified. Additionally, simultaneous fluoroscopic and nuclear images of a sphere phantom were acquired with a physical prototype system and compared with the simulations. For small hot spots, contrast is comparable for all simulated collimators. Noise levels are, however, 3 to 8 times higher in pinhole geometries than in parallel

A cross-platform survey of CT image quality and dose from routine abdomen protocols and a method to systematically standardize image quality

PubMed Central

Favazza, Christopher P.; Duan, Xinhui; Zhang, Yi; Yu, Lifeng; Leng, Shuai; Kofler, James M.; Bruesewitz, Michael R.; McCollough, Cynthia H.

2015-01-01

Through this investigation we developed a methodology to evaluate and standardize CT image quality from routine abdomen protocols across different manufacturers and models. The influence of manufacturer-specific automated exposure control systems on image quality was directly assessed to standardize performance across a range of patient sizes. We evaluated 16 CT scanners across our health system, including Siemens, GE, and Toshiba models. Using each practice’s routine abdomen protocol, we measured spatial resolution, image noise, and scanner radiation output (CTDIvol). Axial and in-plane spatial resolutions were assessed through slice sensitivity profile (SSP) and modulation transfer function (MTF) measurements, respectively. Image noise and CTDIvol values were obtained for three different phantom sizes. SSP measurements demonstrated a bimodal distribution in slice widths: an average of 6.2 ± 0.2 mm using GE’s “Plus” mode reconstruction setting and 5.0 ± 0.1 mm for all other scanners. MTF curves were similar for all scanners. Average spatial frequencies at 50%, 10%, and 2% MTF values were 3.24 ± 0.37, 6.20 ± 0.34, and 7.84 ± 0.70 lp/cm, respectively. For all phantom sizes, image noise and CTDIvol varied considerably: 6.5–13.3 HU (noise) and 4.8–13.3 mGy (CTDIvol) for the smallest phantom; 9.1–18.4 HU and 9.3–28.8 mGy for the medium phantom; and 7.8–23.4 HU and 16.0–48.1 mGy for the largest phantom. Using these measurements and benchmark SSP, MTF, and image noise targets, CT image quality can be standardized across a range of patient sizes. PMID:26459751

Intercomparison of methods for image quality characterization. I. Modulation transfer function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samei, Ehsan; Ranger, Nicole T.; Dobbins, James T. III

The modulation transfer function (MTF) and the noise power spectrum (NPS) are widely recognized as the most relevant metrics of resolution and noise performance in radiographic imaging. These quantities have commonly been measured using various techniques, the specifics of which can have a bearing on the accuracy of the results. As a part of a study aimed at comparing the relative performance of different techniques, in this paper we report on a comparison of two established MTF measurement techniques: one using a slit test device [Dobbins et al., Med. Phys. 22, 1581-1593 (1995)] and another using a translucent edge testmore » device [Samei et al., Med. Phys. 25, 102-113 (1998)], with one another and with a third technique using an opaque edge test device recommended by a new international standard (IEC 62220-1, 2003). The study further aimed to substantiate the influence of various acquisition and processing parameters on the estimated MTF. The slit test device was made of 2 mm thick Pb slabs with a 12.5 {mu}m opening. The translucent edge test device was made of a laminated and polished Pt{sub 0.9}Ir{sub 0.1} alloy foil of 0.1 mm thickness. The opaque edge test device was made of a 2 mm thick W slab. All test devices were imaged on a representative indirect flat-panel digital radiographic system using three published beam qualities: 70 kV with 0.5 mm Cu filtration, 70 kV with 19 mm Al filtration, and 74 kV with 21 mm Al filtration (IEC-RQA5). The latter technique was also evaluated in conjunction with two external beam-limiting apertures (per IEC 62220-1), and with the tube collimator limiting the beam to the same area achieved with the apertures. The presampled MTFs were deduced from the acquired images by Fourier analysis techniques, and the results analyzed for relative values and the influence of impacting parameters. The findings indicated that the measurement technique has a notable impact on the resulting MTF estimate, with estimates from the overall IEC

Intercomparison of methods for image quality characterization. I. Modulation transfer function.

PubMed

Samei, Ehsan; Ranger, Nicole T; Dobbins, James T; Chen, Ying

2006-05-01