scholarly journals Numerical evaluation of image parameters of ETR-1

2016 ◽  
Vol 2 (1) ◽  
pp. 489-491
Author(s):  
Shamim Ahmed ◽  
Marian Krüger ◽  
Christian Willomitzer ◽  
Golam A. Zakaria
Keyword(s):  
Image Quality ◽  
Treatment Planning ◽  
Numerical Evaluation ◽  
Numerical Estimation ◽  
Low Contrast ◽  
Precise Result ◽  
Test Tool ◽  
Naked Eye ◽  
Pre Treatment

AbstractIn this work, we developed a method to handle the image quality test-tool precisely. This test-tool is important to evaluate the quality of the medical images for pre-treatment planning phase. But the achieved images are estimated by naked eyes, which does not provide the precise result. Our main goal is to get the desired image parameters numerically. This numerical estimation overcomes the limitation of naked eye observation. Hence, it enhances the pre-treatment planning. The ETR-1 test-tool is considered here. The contrast, the low contrast details and line-pairs (lp/mm) were estimated.

How Good is Too Good? A Subjective Study on Over Enhancement of Images

2021 ◽  
Vol 2021 (29) ◽  
pp. 83-88
Author(s):  
Sahar Azimian ◽  
Farah Torkamani Azar ◽  
Seyed Ali Amirshahi
Keyword(s):  
Image Quality ◽  
High Contrast ◽  
Current Image ◽  
Low Contrast ◽  
Image Dataset ◽  
Long Time ◽  
Reference Images ◽  
Subjective Study ◽  
Contrast Image

For a long time different studies have focused on introducing new image enhancement techniques. While these techniques show a good performance and are able to increase the quality of images, little attention has been paid to how and when overenhancement occurs in the image. This could possibly be linked to the fact that current image quality metrics are not able to accurately evaluate the quality of enhanced images. In this study we introduce the Subjective Enhanced Image Dataset (SEID) in which 15 observers are asked to enhance the quality of 30 reference images which are shown to them once at a low and another time at a high contrast. Observers were instructed to enhance the quality of the images to the point that any more enhancement will result in a drop in the image quality. Results show that there is an agreement between observers on when over-enhancement occurs and this point is closely similar no matter if the high contrast or the low contrast image is enhanced.

scholarly journals The difference in dose and image quality between magnification methods used after the introduction of larger 60-inch operator screens

BJR|Open ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 20190044
Author(s):  
Hywel Mortimer-Roberts ◽  
Michael R Rees
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Communication Systems ◽  
Image Resolution ◽  
Low Contrast ◽  
Test Tool ◽  
Reduce Radiation Dose ◽  
The Difference ◽  
Picture Archiving And Communication ◽  
Area Product

Objective: To determine whether the use of display matrix magnification on larger operator screens without the use of conventional magnification can reduce radiation dose to the patient, and what effect it would have on image quality. Methods: The kerma-area product (KAP) resulting from standard projections in cardiac angiography were measured when an anthropomorphic phantom was imaged using conventional magnification method and display matrix magnification. The image quality was also evaluated by three observers using a TOR 18FG test tool for both magnification method. Results: The mean radiation KAP for the seven views with conventional magnification was 36.65 µGy m−2 whilst a reduction in KAP of 20.4% is possible using display matrix magnification (p < 0.05). The image resolution during acquisition was identical between both methods and only slightly reduced for the display matrix (1.6 LP mm−1) compared to conventional magnification (1.8 LP mm−1) when images were stored and retrieved on a Picture Archiving and Communication Systems (PACS) system. Both methods retained the same low-contrast detectability to PACS, with only a slight increase in detectability of 18 for display matrix magnification compared to 17 for conventional. Conclusion: Using display matrix magnification instead of conventional equipment magnification significantly reduces radiation does in all standard cardiac views without reducing image quality for the operator. This reduction in radiation dose is significant (p < 0.05) for the patients. The resolution did not change during acquisition, but contrast improved slightly (0.9% threshold contrast), but lost resolution of 0.2 LP mm−1 when archived to PACS. Advances in knowledge: This is a new method of reducing significant dose to the patient during cardiology examinations and may encourage further studies in other fluoroscopy lead examination to see if it could work for them.

scholarly journals Quantifying the Utility of Low Resolution Brain Imaging:: Treatment of Infant Hydrocephalus

2021 ◽  
Author(s):  
Joshua Harper ◽  
Venkateswararao Cherukuri ◽  
Tom O'Riley ◽  
Mingzhao Yu ◽  
Edith Mbabazi-Kabachelor ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Treatment Planning ◽  
Image Resolution ◽  
Learning Enhancement ◽  
Low Contrast ◽  
Substantial Risk ◽  
Noise Ratio ◽  
Hydrocephalus Treatment ◽  
Post Hoc

As low-field MRI technology is being disseminated into clinical settings, it is important to assess the image quality required to properly diagnose and treat a given disease. In this post-hoc analysis of an ongoing randomized clinical trial, we assessed the diagnostic utility of reduced-quality and deep learning enhanced images for hydrocephalus treatment planning. Images were degraded in terms of resolution, noise, and contrast between brain and CSF and enhanced using deep learning algorithms. Both degraded and enhanced images were presented to three experienced pediatric neurosurgeons accustomed to working in LMIC for assessment of clinical utility in treatment planning for hydrocephalus. Results indicate that image resolution and contrast-to-noise ratio between brain and CSF predict the likelihood of a useful image for hydrocephalus treatment planning. For images with 128x128 resolution, a contrast-to-noise ratio of 2.5 has a high probability of being useful (91%, 95% CI 73% to 96%; P=2e-16). Deep learning enhancement of a 128x128 image with very low contrast-to-noise (1.5) and low probability of being useful (23%, 95% CI 14% to 36%; P=2e-16) increases CNR improving the apparent likelihood of being useful, but carries substantial risk of structural errors leading to misleading clinical interpretation (CNR after enhancement = 5; risk of misleading results = 21%, 95% CI 3% to 32%; P=7e-11). Lower quality images not customarily considered acceptable by clinicians can be useful in planning hydrocephalus treatment. We find substantial risk of misleading structural errors when using deep learning enhancement of low quality images. These findings advocate for new standards in assessing acceptable image quality for clinical use.

Image Quality of Digital Direct Flat-Panel Mammography Versus an Analog Screen-Film Technique Using a Low-Contrast Phantom

2009 ◽  
Vol 20 (3) ◽  
pp. 271-273
Author(s):  
A. Karellas ◽  
S. Vedantham
Keyword(s):  
Image Quality ◽  
Flat Panel ◽  
Low Contrast

scholarly journals Comparison of image quality of an abdominal acquisition mode of angiography systems from four major manufacturers

2018 ◽  
Vol 5 (2) ◽  
pp. 6
Author(s):  
Lucie Sukupova ◽  
Jan Rydlo ◽  
Ondrej Hlavacek ◽  
Daniel Vedlich ◽  
Jan H. Peregrin
Keyword(s):  
Image Quality ◽  
Line Pair ◽  
Obese Patients ◽  
Clinical Images ◽  
Contrast Resolution ◽  
Low Contrast ◽  
System A ◽  
Acquisition Mode ◽  
Air Kerma Rate

Objective: The aim of this study was to compare image quality of different abdominal acquisition modes under conditions simulating obese patients whose images suffer more from noise and scatter radiation. Images were acquired in clinically used acquisition modes on the static and dynamic phantom for four angiography systems.Methods: A LEGO cart with 34 cm of PMMA and Pro-RTG Fluo18 phantom were used to simulate obese patients. The low-contrast resolution was assessed subjectively by two readers and objectively using signal-difference-to-noise ratio (SDNR) and using SDNR to air kerma rate. The line-pair resolution was assessed using the transmitted contrast value for line-pair groups.Results: Systems use different exposure parameters and dose but they differ in postprocessing too. Qualitative and quantitative assessments of noise produced similar results, images produced by systems A and C were noisier than by systems B and D. Highest SDNR was provided by System B, whilst System A produced the lowest values, which were almost the same for objects with different contrast. The image quality was affected mainly by frame lengths and postprocessing, but also by the dose. The images of the static phantom were better compared to the images of the dynamic phantom, which was an expected result.Conclusions: It was possible to identify image quality differences and to characterize features of postprocessing from measurements on standardized objects. A potential for optimization on some systems was identified, although further work, including assessment of clinical images, would be needed as part of the optimization process.

Diagnostic performance and image quality of low-tube voltage and low-contrast medium dose protocol with hybrid iterative reconstruction for hepatic dynamic CT

2021 ◽  
Author(s):  
Shintaro Ichikawa ◽  
Utaroh Motosugi ◽  
Tatsuya Shimizu ◽  
Marie Luise Kromrey ◽  
Yoshihito Aikawa ◽  
...  
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Diagnostic Performance ◽  
Dynamic Ct ◽  
Diagnostic Ability ◽  
Tube Voltage ◽  
Low Contrast ◽  
Lesion Detectability ◽  
Hybrid Iterative Reconstruction

Objective: To evaluate the diagnostic performance and image quality of the low-tube voltage and low-contrast medium dose protocol for hepatic dynamic CT. Methods: This retrospective study was conducted between January and May 2018. All patients underwent hepatic dynamic CT using one of the two protocols: tube voltage, 80 kVp and contrast dose, 370   mgI/kg with hybrid iterative reconstruction or tube voltage, 120 kVp and contrast dose, 600  mgI/kg with filtered back projection. Two radiologists independently scored lesion conspicuity and image quality. Another radiologist measured the CT numbers of abdominal organs, muscles, and hepatocellular carcinoma (HCC) in each phase. Lesion detectability, HCC diagnostic ability, and image quality of the arterial phase were compared between the two protocols using the non-inferiority test. CT numbers and HCC-to-liver contrast were compared between the protocols using the Mann–Whitney U test. Results: 424 patients (70.5 ± 10.1 years) were evaluated. The 80-kVp protocol showed non-inferiority in lesion detectability and diagnostic ability for HCC (sensitivity, 85.7–89.3%; specificity, 96.3–98.6%) compared with the 120-kVp protocol (sensitivity, 91.0–93.3%; specificity, 93.6–97.3%) (p < 0.001–0.038). The ratio of fair image quality in the 80-kVp protocol also showed non-inferiority compared with that in the 120-kVp protocol in assessments by both readers (p < 0.001). HCC-to-liver contrast showed no significant differences for all phases (p = 0.309–0.705) between the two protocols. Conclusion: The 80-kVp protocol with hybrid iterative reconstruction for hepatic dynamic CT can decrease iodine doses while maintaining diagnostic performance and image quality compared with the 120-kVp protocol. Advances in knowledge: The 80- and 120-kVp protocols showed equivalent hepatic lesion detectability, diagnostic ability for HCC, image quality, and HCC-to-liver contrast. The 80-kVp protocol showed a 38.3% reduction in iodine dose compared with the 120-kVp protocol.

Image quality of intraoral radiographs used by general practitioners in prosthodontic treatment planning.

1994 ◽  
Vol 23 (1) ◽  
pp. 46-48 ◽  
Author(s):  
B Svenson ◽  
T Eriksson ◽  
M Kronström ◽  
S Palmqvist
Keyword(s):  
Image Quality ◽  
Treatment Planning ◽  
General Practitioners

Automatic analysis of image quality by ETR-1 for the On-Board Imager

2020 ◽  
Vol 65 (1) ◽  
pp. 99-105
Author(s):  
Shamim Ahmed ◽  
Marian Krüger ◽  
Christian Willomitzer ◽  
Golam Abu Zakaria
Keyword(s):  
Image Quality ◽  
Patient Positioning ◽  
Modulation Transfer ◽  
Test Plate ◽  
Low Contrast ◽  
Test Tool ◽  
Rotation Mode ◽  
Slight Rotation ◽  
Binary Masking ◽  
The Ideal

AbstractThe test-plate image of an image quality test tool is processed. The processing is based on quality assurance with the well-established test device ETR-1. A program is developed to analyze the parameters such as contrast, low contrast and resolution automatically. This results in more accurate patient positioning for the On-Board Imager (OBI) system. The contrast and resolution are measured by means of Bresenham’s line algorithm. The low contrast is calculated with the help of binary masking. The modulation transfer function (MTF) is also observed for the system. The developed program imports the Digital Imaging and Communications in Medicine (DICOM) image and returns the image parameters. The program can process the ideal image or the less noisy image. The no-rotation-mode or the slight-rotation-mode of the test-plate can be analyzed.

scholarly journals Lab Image and Field Image Contrast Quality Differentiation

2020 ◽  
Vol 9 (3) ◽  
pp. 3428-3431
Keyword(s):  
Image Quality ◽  
System Performance ◽  
Input Image ◽  
Image Size ◽  
Standard Size ◽  
Low Contrast ◽  
Quality Differentiation ◽  
Image Dimension ◽  
Processing Material

Image processing performance can be improved with the process of resizing the original input image to one standard size. Most of the previous studies used a standard size of 256 x 256 to provide the image as the image pre-processing material. The result of different image size dimension are shows in this research to proven that image resizing is important. Reducing image dimension size can help to improve system performance. At the same time, it is importance to keep the image quality. This study shows that by reducing image dimension, it can improve the computer or system performance more than 95%. Image quality can be measured to get helpful information for the study after resizing the image into the same standard size. In this study, measurement of contrast levels was taken to compare the quality differences between image labs and field images. It turns out that the quality of lab image produces high-quality images with good brightness over image field image.The best quality image is the images that have low contrast. Therefore in this research paper we used CLAHE method to enhance the contrast and brightness for field image.

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