Retrospective Assessment of the Impact of Primary Language Video Instructions on Image Quality of Abdominal MRI

2021 ◽  
Author(s):  
Myles T. Taffel ◽  
Andrew B. Rosenkrantz ◽  
Jonathan A. Foster ◽  
Jay A. Karajgikar ◽  
Paul N. Smereka ◽  
...  
Keyword(s):  
Image Quality ◽  
Primary Language ◽  
Retrospective Assessment ◽  
Abdominal Mri ◽  
The Impact

scholarly journals Modeling and image quality enhancement for dynamic compressive imaging system

2021 ◽  
Vol 15 ◽  
pp. 174830262110080
Author(s):  
Changjun Zha* ◽  
Qian Zhang* ◽  
Huimin Duan
Keyword(s):  
Image Quality ◽  
Imaging System ◽  
Quality Enhancement ◽  
Target Image ◽  
Compressive Imaging ◽  
Image Quality Enhancement ◽  
System A ◽  
Single Column ◽  
The Impact

Traditional single-pixel imaging systems are aimed mainly at relatively static or slowly changing targets. When there is relative motion between the imaging system and the target, sizable deviations between the measurement values and the real values can occur and result in poor image quality of the reconstructed target. To solve this problem, a novel dynamic compressive imaging system is proposed. In this system, a single-column digital micro-mirror device is used to modulate the target image, and the compressive measurement values are obtained for each column of the image. Based on analysis of the measurement values, a new recovery model of dynamic compressive imaging is given. Differing from traditional reconstruction results, the measurement values of any column of vectors in the target image can be used to reconstruct the vectors of two adjacent columns at the same time. Contingent upon characteristics of the results, a method of image quality enhancement based on an overlapping average algorithm is proposed. Simulation experiments and analysis show that the proposed dynamic compressive imaging can effectively reconstruct the target image; and that when the moving speed of the system changes within a certain range, the system reconstructs a better original image. The system overcomes the impact of dynamically changing speeds, and affords significantly better performance than traditional compressive imaging.

Impact of total variation regularized expectation maximization reconstruction on the image quality of 68Ga-PSMA PET: a phantom and patient study

2021 ◽  
pp. 20201356
Author(s):  
Feng-Jiao Yang ◽  
Shu-Yue Ai ◽  
Runze Wu ◽  
Yang Lv ◽  
Hui-Fang Xie ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Quality ◽  
Total Variation ◽  
Expectation Maximization ◽  
Image Noise ◽  
Psma Pet ◽  
Pet Ct ◽  
Digital Pet ◽  
The Impact

Objectives: To investigate the impact of total variation regularized expectation maximization (TVREM) reconstruction on the image quality of 68Ga-PSMA-11 PET/CT using phantom and patient data. Methods: Images of a phantom with small hot sphere inserts and 20 prostate cancer patients were acquired with a digital PET/CT using list-mode and reconstructed with ordered subset expectation maximization (OSEM) and TVREM with seven penalisation factors between 0.01 and 0.42 for 2 and 3 minutes-per-bed (m/b) acquisition. The contrast recovery (CR) and background variability (BV) of the phantom, image noise of the liver, and SUVmax of the lesions were measured. Qualitative image quality was scored by two radiologists using a 5-point scale (1-poor, 5-excellent). Results: The performance of CR, BV, and image noise, and the gain of SUVmax was higher for TVREM 2 m/b groups with the penalization of 0.07 to 0.28 compared to OSEM 3 m/b group (all p < 0.05). The image noise of OSEM 3 m/b group was equivalent to TVREM 2 and 3 m/b groups with a penalization of 0.14 and 0.07, while lesions’ SUVmax increased 15 and 20%. The highest qualitative score was attained at the penalization of 0.21 (3.30 ± 0.66) for TVREM 2 m/b groups and the penalization 0.14 (3.80 ± 0.41) for 3 m/b group that equal to or greater than OSEM 3 m/b group (2.90 ± 0.45, p = 0.2 and p < 0.001). Conclusions: TVREM improves lesion contrast and reduces image noise, which allows shorter acquisition with preserved image quality for PSMA PET/CT. Advances in knowledge: TVREM reconstruction with optimized penalization factors can generate higher quality PSMA-PET images for prostate cancer diagnosis.

THE IMPACT OF HEAD POSITIONING ON THE IMAGE QUALITY OF MULTI-DETECTOR COMPUTED TOMOGRAPHY

2021 ◽  
pp. 2150050
Author(s):  
Yang-Ting Hsu ◽  
Jo-Chi Jao
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Control Group ◽  
Ct Scanner ◽  
Head Ct ◽  
Radiologic Technologists ◽  
Head Positioning ◽  
The Impact ◽  
Multi Detector Computed Tomography

Radiologic technologists face various types of patients during multi-detector computed tomography (CT) examinations. In emergency departments, it is common to have patients who cannot follow instructions for the examinations. The asymmetric axial view of the head CT might affect the correctness of the clinician’s diagnosis. This study aimed to assess the impact of head positioning on the image quality of head CT using two phantoms. All scans were performed on a 16-slice CT scanner. In the control group, the tilted angle of the phantoms was 0[Formula: see text], and no multiplanar reconstruction (MPR) was performed. In the experimental groups, the tilted angles of the phantoms were 5[Formula: see text], 10[Formula: see text] and 15[Formula: see text], respectively, and MPR was performed afterwards. The results showed that if the head was tilted during the head CT examinations, image asymmetry and artifacts appeared without MPR. After MPR, one phantom showed that there were significant differences and the other phantom showed no significant differences quantitatively in image symmetry and artifacts between experimental groups and the control group, while both phantoms showed no significant differences qualitatively in image symmetry and artifacts between experimental groups and the control group. Although MPR can correct the image asymmetry and artifacts caused by tilted head positioning to some extent, it consumes time. Therefore, technologists should position the head as exactly as possible when performing head CT examinations.

scholarly journals Utilization of sinogram affirmed iterative reconstruction on 128 multi slice computed tomography scan to reduce radiation dose and improve image quality on thorax multi slice computed tomography scan: chest phantom study

2019 ◽  
Vol 6 (10) ◽  
pp. 4533
Author(s):  
Halinda Fatmayanti ◽  
Kusworo Adi ◽  
Yeti Kartikasari
Keyword(s):  
Computed Tomography ◽  
Experimental Study ◽  
Image Quality ◽  
Radiation Dose ◽  
Dose Assessment ◽  
Computed Tomography Scan ◽  
Tube Voltage ◽  
The Impact ◽  
Tomography Scan

Background: Thorax MSCT examination is a diagnostic imaging that is capable of displaying both normal and pathological lung and respiratory organs. MSCT examination also has a better level of sensitivity and specificity compared to other modalities, but the radiation exposure given is very high, so the radiation dose given to patients is high. The reduction in radiation dose is very important because of the direct exposure to sensitive tissue. One method of reducing radiation dose is by reducing the tube voltage. However, the decrease in tube voltage causes a decrease in image quality as indicated by increased noise and decreased CNR. To maintain the quality of the image at low tube voltage setting, an IR reconstruction of SAFIRE was used. The purpose of this research is to know the impact of using SAFIRE on dose radiation and image quality of thorax MSCT.Methods: This study was an experimental study with a quasi-experimental study design. The object used was the N-1 Lungman chest phantom in which an artificial tumor was attached. Radiation dose assessment used CTDI value, while image quality assessment used noise and CNR. Data processing was conducted using linear regression test.Results: There was an effect of tube voltage setting and SAFIRE setting on radiation dose and image quality.Conclusions: Tube voltage ssetting and SAFIRE setting had an effect on radiation dose and image quality. Tube voltage setting and SAFIRE strength level setting that were able to provide optimal radiation dose and image quality were tube voltage of 80 kVp and SAFIRE strength levels 3 and 4 (S3 and S4). 

scholarly journals NO-REFERENCE IMAGE QUALITY ASSESSMENT FOR ZY3 IMAGERY IN URBAN AREAS USING STATISTICAL MODEL

2016 ◽  
Vol XLI-B3 ◽  
pp. 949-954 ◽  
Author(s):  
Y. Zhang ◽  
W.H. Cui ◽  
F. Yang ◽  
Z.C. Wu
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Urban Areas ◽  
Satellite Images ◽  
Image Quality Assessment ◽  
Reference Image ◽  
Atmospheric Conditions ◽  
Natural Scene Statistics ◽  
The Impact

More and more high-spatial resolution satellite images are produced with the improvement of satellite technology. However, the quality of images is not always satisfactory for application. Due to the impact of complicated atmospheric conditions and complex radiation transmission process in imaging process the images often suffer deterioration. In order to assess the quality of remote sensing images over urban areas, we proposed a general purpose image quality assessment methods based on feature extraction and machine learning. We use two types of features in multi scales. One is from the shape of histogram the other is from the natural scene statistics based on Generalized Gaussian distribution (GGD). A 20-D feature vector for each scale is extracted and is assumed to capture the RS image quality degradation characteristics. We use SVM to learn to predict image quality scores from these features. In order to do the evaluation, we construct a median scale dataset for training and testing with subjects taking part in to give the human opinions of degraded images. We use ZY3 satellite images over Wuhan area (a city in China) to conduct experiments. Experimental results show the correlation of the predicted scores and the subjective perceptions.

Looks Clear and Sounds Familiar: How Consumers Form Inferential Beliefs About Luxury Hotel Service Quality

2021 ◽  
pp. 193896552110168
Author(s):  
Sann Ryu ◽  
Yun-na Park ◽  
Jungkun Park
Keyword(s):  
Image Quality ◽  
Service Quality ◽  
Image Resolution ◽  
Processing Fluency ◽  
Photographic Image ◽  
Brand Familiarity ◽  
Proposed Model ◽  
Luxury Hotel ◽  
The Impact

The purpose of this study is to examine how varying levels of brand familiarity and photographic image quality of hotel pictures influence consumers’ perceptions about luxury hotel services and attitudinal responses and whether their visual aesthetic experience and inferential beliefs about service quality can mediate such effects. This is a 2 (brand familiarity: familiar vs. unfamiliar brand) × 2 (image quality: high vs. low image resolution) factorial design randomized experiment and the proposed model was tested using a structural equation model ( N = 430). The proposed model was confirmed that consumers viewed the visual appearance of a hotel suite room (varying in image quality) and brand name (varying in brand familiarity), experienced processing fluency, drew inferential beliefs (about tangible and intangible service quality), formed attitudes toward the brand, and purchase intentions. The study presents an explanatory framework that delineates how varying hotel-related cues in an online setting can shape consumers’ perceptions and judgments of a luxury hotel brand. To one’s best knowledge, no research has examined the impact of both brand familiarity and photographic image quality of a hotel room. More importantly, this study reveals to what extent consumers’ inferential beliefs about service quality can be influenced by the heuristic cues and provides direct evidence for the mediating role of processing fluency and aesthetic appreciation.

scholarly journals The Impact of IOL Abbe Number on Polychromatic Image Quality of Pseudophakic Eyes

2020 ◽  
Vol Volume 14 ◽  
pp. 2271-2281
Author(s):  
Arthur Bradley ◽  
Renfeng Xu ◽  
Huachun Wang ◽  
Mateusz Jaskulski ◽  
Xin Hong ◽  
...  
Keyword(s):  
Image Quality ◽  
The Impact

scholarly journals The Impact of Varying Number of OSEM Iterations on Standardized Uptake Value and Image Quality of Discovery STE PET/CT Scanner

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 68s-68s
Author(s):  
B. Ali ◽  
A. Afshan ◽  
M.B. Kakakhel
Keyword(s):  
Image Quality ◽  
Standardized Uptake Value ◽  
Acquisition Time ◽  
List Mode ◽  
Ct Scanner ◽  
Matrix Size ◽  
Cold Lesion ◽  
Pet Ct ◽  
The Impact

Background: In PET imaging both quantitative and qualitative interpretations are used. Qualitative and quantitative interpretations depend upon PET/CT image quality that along with many biologic factors strongly depends upon image reconstruction parameters. Aim: The objective of this experimental work was to study the impact of one of the key reconstruction parameter, i.e., number of reconstruction iteration, on standardized uptake value and image quality of PET/CT scan. Methods: Images of NEMA IEC Image Quality Phantom were acquired in list mode for 10 mins on Discovery STE PET/CT scanner, using tumor to background ratio of 4:1 and 18F-FDG as radiotracer. List mode data were further transformed into data sets of varying acquisition time (0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0 mins) per bed position. Transformed data set of 5.0 mins were used to study the impact of varying number of iterations (2, 3, 4, 5, 7, 10, 15, 20) using OSEM approach of iterative reconstruction. Standardized uptake value (SUV) and underestimation in SUV were calculated as quantitative measures, while hot lesion contrast, cold lesion contrast and background variability were calculated as qualitative measures. Results: Standardized uptake value, hot and cold lesion contrast, image spatial resolution and background variability showed increasing trend with increase in reconstruction iterations. Maximum increase of 20.25%, 16.33%, 9.79% and 6.88% was observed in SUV for 10 mm, 13 mm, 17 mm and 22 mm lesions as number of iteration change from 2 to 3. Smallest and the largest diameter lesions showed maximum underestimations of 54.67% and 8.20% at 2 iterations respectively. Percentage hot lesion contrast showed rapid increase as the number of iteration change from 2 to 7 and increased slowly afterward. Background variability range from 4.4% to 6.4%, 4.1%–5.7%, 3.6%–4.6%, 3%–3.8%, 2.7%–3.2%, 2.4%–2.7% for 10.0 mm, 13.0 mm, 17.0 mm, 22.0 mm, 28.0 mm and 37.0 mm sphere respectively. Conclusion: Optimized reconstruction parameters for routine clinical studies 3 iterations with image matrix size of 128 × 128 with filters FWHM of 6 mm and for high resolution studies 3 iterations image matrix size of 256×256 with filters FWHM of 6 mm.

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