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.

The Influence of Alteration of kVp and mAs towards the Image Quality of Acrylic Using CBCT

2019 ◽  
Vol 829 ◽  
pp. 252-257
Author(s):  
Azhari ◽  
Yohanes Hutasoit ◽  
Freddy Haryanto
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Region Of Interest ◽  
Signal To Noise ◽  
Bite Block ◽  
Significant Difference ◽  
Noise Ratio ◽  
Post Hoc ◽  
Radiograph Image

CBCT is a modernized technology in producing radiograph image on dentistry. The image quality excellence is very important for clinicians to interpret the image, so the result of diagnosis produced becoming more accurate, appropriate, thus minimizing the working time. This research was aimed to assess the image quality using the blank acrylic phantom polymethylmethacrylate (PMMA) (C­5H8O2)n in the density of 1.185 g/cm3 for evaluating the homogeneity and uniformity of the image produced. Acrylic phantom was supported with a tripod and laid down on the chin rest of the CBCT device, then the phantom was fixed, and the edge of the phantom was touched by the bite block. Furthermore, the exposure of the X-ray was executed toward the acrylic phantom with various kVp and mAs, from 80 until 90, with the range of 5 kV and the variation of mA was 3, 5, and 7 mA respectively. The time exposure was kept constant for 25 seconds. The samples were taken from CBCT acrylic images, then as much as 5 ROIs (Region of Interest) was chosen to be analyzed. The ROIs determination was analyzed by using the ImageJ® software for recognizing the influence of kVp and mAs towards the image uniformity, noise and SNR. The lowest kVp and mAs had the result of uniformity value, homogeneity and signal to noise ratio of 11.22; 40.35; and 5.96 respectively. Meanwhile, the highest kVp and mAs had uniformity value, homogeneity and signal to noise ratio of 16.96; 26.20; and 5.95 respectively. There were significant differences between the image uniformity and homogeneity on the lowest kVp and mAs compared to the highest kVp and mAs, as analyzed with the ANOVA statistics analysis continued with the t-student post-hoc test with α = 0.05. However, there was no significant difference in SNR as analyzed with the ANOVA statistic analysis. The usage of the higher kVp and mAs caused the improvement of the image homogeneity and uniformity compared to the lower kVp and mAs.

scholarly journals Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography

2021 ◽  
Vol 94 (1117) ◽  
pp. 20200677
Author(s):  
Andrea Steuwe ◽  
Marie Weber ◽  
Oliver Thomas Bethge ◽  
Christin Rademacher ◽  
Matthias Boschheidgen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Dose Reduction ◽  
Low Dose ◽  
Ct Images ◽  
Image Noise ◽  
The Novel ◽  
Subjective Image Quality ◽  
Image Information ◽  
Noise Ratio

Objectives: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. Methods: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. Results: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. Conclusion: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. Advances in knowledge: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information. The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.

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 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.

scholarly journals Studies on the radiation dose, image quality and low contrast detectability from MSCT abdomen by using low tube voltage

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
A. Mokhtar ◽  
Z. A. Aabdelbary ◽  
A. Sarhan ◽  
H. M. Gad ◽  
M. T. Ahmed
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Statistical Significance ◽  
Image Noise ◽  
Tube Voltage ◽  
Current Time ◽  
Low Contrast ◽  
Low Tube Voltage ◽  
Tube Current ◽  
Noise Ratio

Abstract Background To study radiation dose, image quality and low-contrast cylinder detectability from multislice CT (MSCT) abdomen by using low tube voltage using the American College of Radiology (ACR) phantom. The ACR phantom (low-contrast module) was scanned with 64 MSCT scanner (Brilliance, Philips Medical System, Eindhoven, Netherlands) with 80 and 120 KVP, utilizing different tube current time product (mAs) range from 50 to 380 mAs. The image noise (SD), signal to noise ratio, contrast-to-noise ratio (CNR), and scores of low contrast detectability were assessed for every image respectively. Results From images analyses, the noise essentially increased with the use of low tube voltage. The CNR was 0.94 ± 0.27 at 120 KVP, and CNR was 0.43 ± 0.22 at 80 KVP. However, with the same dose, there were no differences of statistical significance in scores of low-contrast detectability between 120 KVP at 300mAs and 80 KVP at (200–380) mAs (p > 0.05). At 300 mAs, the CTDIvol obtained at 80 KVP was about 29% of that at 120 KVP. The CTDIvol obtained at 80 KVP were decreased from 5% at 50 mAs, to 37% at 380 mAs. Conclusions There is a possibility to decrease exposure of radiation virtually by reducing KVP from 120 to 80 KVP in examination of abdominal CT when the high tube current is used, though increasing image noise at low tube voltage.

scholarly journals Applicability of deep learning-based reconstruction trained by brain and knee 3T MRI to lumbar 1.5T MRI

2021 ◽  
Vol 10 (6) ◽  
pp. 205846012110239
Author(s):  
Nobuo Kashiwagi ◽  
Hisashi Tanaka ◽  
Yuichi Yamashita ◽  
Hiroto Takahashi ◽  
Yoshimori Kassai ◽  
...  
Keyword(s):  
Deep Learning ◽  
Magnetic Resonance ◽  
Image Quality ◽  
Signal To Noise Ratio ◽  
Magnetic Resonance Images ◽  
Reconstruction Method ◽  
Signal To Noise ◽  
Scanning Time ◽  
Noise Ratio ◽  
Weighted Sequences

Background Several deep learning-based methods have been proposed for addressing the long scanning time of magnetic resonance imaging. Most are trained using brain 3T magnetic resonance images, but is unclear whether performance is affected when applying these methods to different anatomical sites and at different field strengths. Purpose To validate the denoising performance of deep learning-based reconstruction method trained by brain and knee 3T magnetic resonance images when applied to lumbar 1.5T magnetic resonance images. Material and Methods Using a 1.5T scanner, we obtained lumber T2-weighted sequences in 10 volunteers using three different scanning times: 228 s (standard), 119 s (double-fast), and 68 s (triple-fast). We compared the images obtained by the standard sequence with those obtained by the deep learning-based reconstruction-applied faster sequences. Results Signal-to-noise ratio values were significantly higher for deep learning-based reconstruction-double-fast than for standard and did not differ significantly between deep learning-based reconstruction-triple-fast and standard. Contrast-to-noise ratio values also did not differ significantly between deep learning-based reconstruction-triple-fast and standard. Qualitative scores for perceived signal-to-noise ratio and overall image quality were significantly higher for deep learning-based reconstruction-double fast and deep learning-based reconstruction-triple-fast than for standard. Average scores for sharpness, contrast, and structure visibility were equal to or higher for deep learning-based reconstruction-double-fast and deep learning-based reconstruction-triple-fast than for standard, but the differences were not statistically significant. The average scores for artifact were lower for deep learning-based reconstruction-double-fast and deep learning-based reconstruction-triple-fast than for standard, but the differences were not statistically significant. Conclusion The deep learning-based reconstruction method trained by 3T brain and knee images may reduce the scanning time of 1.5T lumbar magnetic resonance images by one-third without sacrificing image quality.

Performance Evaluation of Two Iterative Reconstruction Algorithms--MBIR and ASIR, in Low Radiation Dose and Low Contrast Dose Abdominal CT in Children

2019 ◽  
Author(s):  
Jihang Sun ◽  
Lixin Yang ◽  
Zuofu Zhou ◽  
Dan Zhang ◽  
Wei Han ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Iterative Reconstruction ◽  
Image Noise ◽  
Abdominal Ct ◽  
Low Contrast ◽  
Low Radiation Dose ◽  
Contrast Dose ◽  
Contrast Enhanced Ct ◽  
Noise Ratio

Abstract Background The adverse effect of low-dose CT on image quality may be mitigated using iterative reconstructions. The purpose of this study was to evaluate the performance of the full model-based iterative reconstruction (MBIR) and adaptive statistical reconstruction (ASIR) algorithms in low radiation dose and low contrast dose abdominal contrast-enhanced CT (CECT) in children. Methods A total of 59 children (32 males and 27 females) undergoing low radiation dose (100kVp) and low contrast dose (270 mgI/ml) abdominal CECT were enrolled. The median age was 4.0 years (ranging from 0.3 to 13 years). The raw data were reconstructed with MBIR, ASIR and filtered back projection (FBP) algorithms into 6 groups (MBIR, 100%ASIR, 80%ASIR, 60%ASIR, 40%ASIR and FBP). The CT numbers, standard deviations, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of liver, pancreas, kidney and abdominal aorta were measured. Two radiologists independently evaluated the subjective image quality including the overall image noise and structure display ability on a 4-point scale with 3 being clinically acceptable. The measurements among the reconstruction groups were compared using one-way ANOVA. Results The overall image noise score and display ability were 4.00±0.00 and 4.00±0.00 with MBIR, and 3.27±0.33 and 3.25±0.43 with ASIR100%, respectively, which met the diagnostic requirement; other reconstructions couldn’t meet the diagnostic requirements. Compared with FBP images, the noise of MBIR images was reduced by 62.86%-65.73% for the respective organs (F=48.15-80.47, P<0.05), and CNR increased by 151.38%-170.69% (F=22.94-38.02, P<0.05). Conclusions MBIR or ASIR100% improves the image quality of low radiation dose and contrast dose abdominal CT in children to meet the diagnostic requirements, and MBIR has the best performance.

OPTIMISATION OF PATIENT DOSE AND IMAGE QUALITY IN FLUOROSCOPICALLY GUIDED CERVICAL SPINE SURGERY: A PHANTOM-BASED STUDY

2018 ◽  
Vol 184 (2) ◽  
pp. 237-247 ◽  
Author(s):  
Vasileios I Metaxas ◽  
Gerasimos A Messaris ◽  
George D Gatzounis ◽  
George S Panayiotakis
Keyword(s):  
Image Quality ◽  
Spinal Surgery ◽  
Patient Dose ◽  
Skin Dose ◽  
High Contrast ◽  
Operational Parameters ◽  
High Definition ◽  
Low Contrast ◽  
Cervical Spine Surgery ◽  
Noise Ratio

Abstract The purpose of the current study was to provide useful data, which may help neurosurgeons to manage the patient dose and image quality in spinal surgery procedures, utilising a phantom and a test object. The kerma area product, cumulative dose (CD) and entrance surface dose (ESD) rate on the phantom and image intensifier were measured, for selectable fields of view (FOVs), fluoroscopy modes, two geometric magnifications and various phantom thicknesses. The images were subjectively evaluated regarding low-contrast detectability and high-contrast resolution. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), high-contrast spatial resolution (HCSR) and figure of merit (FOM) values were also estimated. The ESD rates increased with increasing phantom thickness, when using electronic or geometric magnification, continuous or high-definition fluoroscopy (HDF). The observers’ evaluation showed relatively slight changes in image quality when pulsed fluoroscopy was used. SNR, CNR and HCSR values decreased with increasing phantom thicknesses, while remained almost constant when using pulsed fluoroscopy. SNR and HCSR improved in HDF, while the CNR remained almost constant only for the FOVs 23 and 17 cm. By applying electronic magnification, this resulted in improved HCSR. FOM values decreased in HDF, with increasing phantom thickness and using electronic magnification. For the ‘thinnest’ patients, CD may overestimate skin dose by 25% than the actual values. Geometric magnification resulted in improved FOM, especially for low-dose fluoroscopy and FOV 23 cm. The knowledge of the increments in dose values, image quality and FOM indices concerning phantom thickness may help neurosurgeons to optimise spinal surgery procedures by selecting the appropriate operational parameters, which could contribute toward the establishment of a radiation protection culture.

scholarly journals Image Quality Evaluation of a Digital Radiography System Made in Thailand

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Udomchai Techavipoo ◽  
Nattawut Sinsuebphon ◽  
Sakunrat Prompalit ◽  
Saowapak Thongvigitmanee ◽  
Walita Narkbuakaew ◽  
...  
Keyword(s):  
Image Quality ◽  
Digital Radiography ◽  
Technology Development ◽  
Image Resolution ◽  
Average Score ◽  
Body Parts ◽  
High Contrast ◽  
Low Contrast ◽  
Contrast Image ◽  
Better Than

Background. The National Science and Technology Development Agency (NSTDA) in Thailand researched and prototyped digital radiography systems under the brand name BodiiRay aiming for sustainable development and affordability of medical imaging technology. The image restoration and enhancement were implemented for the systems. Purpose. The image quality of the systems was evaluated using images from phantoms and from healthy volunteers. Methods. The survey phantom images from BodiiRay and other two commercial systems using the exposure settings for the chest, the abdomen, and the extremity were evaluated by three experience observers in terms of the high-contrast image resolution, the low-contrast image detectability, and the grayscale differentiation. The volunteer images of the chests, the abdomens, and the extremities from BodiiRay were evaluated by three specialized radiologists based on visual grading on 5-point scaled questionnaires for the anatomy visibility, the image quality satisfaction, and the diagnosis confidence in using the images. Results. BodiiRay phantom results were similar to those from the commercial systems. The overall performance averaged across the exposure settings showed that BodiiRay was slightly better than Fujifilm FDR Go in the low-contrast detectability ( p = 0.033 ) and in the grayscale differentiation ( p = 0.004 ). It was also slightly better than Siemens YSIO Max in the high-contrast resolution ( p = 0.018 ). The images of chest, pelvis, and hand phantoms illustrated comparable visual quality. For volunteer images, the percentage of the images scored ≥4 ranged from 61% to 99%, 23% to 92%, and 96% to 99% for the chest, abdomen, and extremity images, respectively. The average score ranged from 3.63 to 4.46, 3.18 to 4.21, and 4.41 to 4.51 for the chest, abdomen, and extremity images, respectively. Conclusion. The phantom image results showed the comparability of these systems. The clinical evaluation showed BodiiRay images provided sufficient image qualities for digital radiography of these body parts.

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