scholarly journals Sparse Bilateral Denoising for CT Scan Images with Edge Preservation

2019 ◽  
Vol 8 (6S) ◽  
pp. 384-387
Keyword(s):  
Image Quality ◽  
Ct Scan ◽  
Sparse Representation ◽  
Bilateral Filter ◽  
Ct Images ◽  
Edge Preservation ◽  
X Ray ◽  
Surgical Clips ◽  
Pruning Algorithms

Denoising in CT images using bilateral with sparse representation is presented in this paper. Artifacts occurs in images when an X-ray penetrates the thick objects like bones, implanted organs, surgical clips etc.,. Due to these artifacts in images , the quality of artifact pruning algorithms will be diminished. In order to preserve the image quality as well as edge details, a bilateral filter along with sparse representation is proposed to reduce the noises. The proposed technique is applied to CT humorous bone image and has achieved the better PSNR of 22dB approximately for 512 x512 image as compared to bicubic filter. The simulated real datasets are used to quantitatively evaluate the noise. Moreover the proposed denoising approach can outperform the latest approach in terms of fidelity

Deep Learning Enabled Deblurring of Computed Tomography Images of Porous Media

2021 ◽  
Author(s):  
Khalid Labib Alsamadony ◽  
Ertugrul Umut Yildirim ◽  
Guenther Glatz ◽  
Umair bin Waheed ◽  
Sherif M. Hanafy
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Transfer Learning ◽  
Temporal Resolution ◽  
Exposure Time ◽  
Ct Images ◽  
Loss Functions ◽  
High Quality ◽  
X Ray ◽  
Training Images

Abstract Computed tomography (CT) is an important tool to characterize rock samples allowing quantification of physical properties in 3D and 4D. The accuracy of a property delineated from CT data is strongly correlated with the CT image quality. In general, high-quality, lower noise CT Images mandate greater exposure times. With increasing exposure time, however, more wear is put on the X-Ray tube and longer cooldown periods are required, inevitably limiting the temporal resolution of the particular phenomena under investigation. In this work, we propose a deep convolutional neural network (DCNN) based approach to improve the quality of images collected during reduced exposure time scans. First, we convolve long exposure time images from medical CT scanner with a blur kernel to mimic the degradation caused because of reduced exposure time scanning. Subsequently, utilizing the high- and low-quality scan stacks, we train a DCNN. The trained network enables us to restore any low-quality scan for which high-quality reference is not available. Furthermore, we investigate several factors affecting the DCNN performance such as the number of training images, transfer learning strategies, and loss functions. The results indicate that the number of training images is an important factor since the predictive capability of the DCNN improves as the number of training images increases. We illustrate, however, that the requirement for a large training dataset can be reduced by exploiting transfer learning. In addition, training the DCNN on mean squared error (MSE) as a loss function outperforms both mean absolute error (MAE) and Peak signal-to-noise ratio (PSNR) loss functions with respect to image quality metrics. The presented approach enables the prediction of high-quality images from low exposure CT images. Consequently, this allows for continued scanning without the need for X-Ray tube to cool down, thereby maximizing the temporal resolution. This is of particular value for any core flood experiment seeking to capture the underlying dynamics.

scholarly journals LO68: Patterns and predictors of emergency physician productivity

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S30-S31
Author(s):  
S. Campbell ◽  
S. Weerasinghe
Keyword(s):  
Emergency Department ◽  
Quality Of Care ◽  
Ct Scan ◽  
Resource Utilization ◽  
Emergency Physician ◽  
X Ray ◽  
Workload Measurement ◽  
Number Of Patients ◽  
Return Visits

Introduction: Emergency Physician (EP) performance comprises both quality of care and quantity of patients seen in a set time. Emergency Department (ED) overcrowding increases the importance of the ability of EPs to see patients as rapidly as is safely possible. Maximizing efficiency requires an understanding of variables that are associated with individual physician performance. While using the incidence of return visits within 48 hours as a quality measure is controversial, repeat visits do consume ED resources. Methods: We analysed the practice variables of 85 EPs working at a single academic ED, for the period from June 1, 2013 to May 31, 2017, using data from an emergency department information system (EDIS). Variables analysed included: number of shifts worked, number of patients seen per hour (pt/hr), an adjusted workload measurement (assigning a higher score to CTAS 1-3 patients), percentage of patients whose care involved an ED learner, and the percentage of patients who returned to the ED within 48 hours of ED discharge. Resource utilization was measured by percentage of diagnostic imaging (ultra sound (US), CT scan (CT), x-ray (XR)) ordered and percentage of patients referred to consulting services. We performed principal component analyses to identify bench marks of resource use, demographic (age, EM qualification, gender) and other practice related predictors of performances. Results: Mean pt/hr differed significantly by EM Qualification for CTAS 2-4, with 1.71/hr (95% Confidence Interval=1.63-1.77) by FRCPS physicians, compared to 1.89/hr by CCFP(EM) (CI=1.81-1.97). There were no differences for CTAS 1 and 5. Other variables associated with a significantly lower pt/hr, included a greater use of imaging, (CT: p=0.0003, XR: p=0.0008) although this was did not reach statistical significance with US (p=0.06%). Female gender, older age, number of patient consultations for CTAS 3 and more patients seen by a learner were all associated with lower pt/hr. Pt/hr was a better predictor (R2=45%) for EP resource utilization than adjusted workload measurement (R2 =35%). Higher use of CT was associated with fewer return visits in <48 hrs (0.13% lower). Male gender, younger age, number of patient consultation for CTAS 3 and fewer patients seen by a learner were all associated with an increase in return visits. Conclusion: We found a significant difference in pt/hr rates and return visits within 48 hours between EPs with different age ranges, gender, and EM certification. Increased use of CT scan and x-ray, and consultation for patients CTAS 3 were associated with lower pt/hr. Return visit rates also varied in association with diagnostic imagine use, age, gender and number of patients seen by a learner. Further research is needed to assess the association with these variables on quality of care.

Image Quality of Reversal-Developed X-Ray Film with Reference to Density

1979 ◽  
Vol 18 (10) ◽  
pp. 1951-1957 ◽  
Author(s):  
Suguru Uchida ◽  
Yoshie Kodera ◽  
Hiroshi Inatsu
Keyword(s):  
Image Quality ◽  
X Ray

Materials And Image Formation In X-ray Lithography

1993 ◽  
Vol 306 ◽  
Author(s):  
F. Cerrina ◽  
G.M. Wells
Keyword(s):  
Image Quality ◽  
Imaging System ◽  
Spatial Coherence ◽  
Image Formation ◽  
Process Variations ◽  
Grain Structure ◽  
Aerial Image ◽  
Transmitted Beam ◽  
X Ray

AbstractIn proximity X-ray lithography there is no imaging system in the traditional sense of the word. There are no mirrors, lenses or other means of manipulating the radiation to form an image from that of a pattern (mask). Rather, in proximity X-ray lithography, mask and imaging systems are one and the same. The radiation that illuminates the mask carries the pattern information in the region of the wavefronts that have been attenuated. The detector (photoresist) is placed so close to the mask itself that the image is formed in the region where diffraction has not yet been able to deteriorate the pattern itself. The quality of the image formation then is controlled directly by the interaction between the mask and the radiation field. In turn, this means that both the illumination field and the mask are critical. The properties of the materials used in making the mask thus play a central role in determining the quality of the image. For instance, edge roughness and slope can strongly influence the image by providing the equivalent of a blur in the diffraction process. This blur is beneficial in reducing the high frequency components in the aerial image but it needs to be controlled and be repeatable. The plating (or other physical deposition) process may create variation in density (and thickness) in the deposited film, that will show up as linewidth variation in the image because of local changes in the contrast; the same applies to variations in the carrier membrane. In the case of subtractive process, variations in edge profile across the mask must be minimized.The variations in material composition, thickness and density may all affect the finale image quality; in the case of the resist, local variations in acid concentration may have strong effect in linewidth control (this effect is of course common to all lithographies).Another place where materials will affect the final image quality is in the condensing system. Mirrors will exhibit some degree of surface roughness, leading to a scattered radiation away from the central (coherent) beam. For scanning systems, this is not harmful since no power is lost in the scattering process and a blur is actually created that reduces the degree of spatial coherence. Filters may also exhibit the same roughness; typically it will not affect the image formation. The presence of surface (changes of reflectivity) or bulk (impurities) defects may however strongly alter the uniformity of the transmitted beam. This is particularly true of rolled Be filters and windows, which may include contaminants of high-Z materials. Hence, the grain structure of the window plays a very important role in determining image uniformity.Finally, a seemingly minor but important area is that of the gas used in the exposure area, typically helium. The gas fulfills several needs: heat exchange medium, to thermally clamp the mask to the wafer; low-loss X-ray transmission medium; protection from reactive oxygen radicals and ozone formation. Small amounts of impurities (air) may have a very strong effect on the transmission, and non-uniform distributions are particularly deleterious.All these factors need to be controlled so that the final image is within the required tolerances. Unfortunately, some of these are difficult to characterize in the visible (e.g., reflectivity variations) and testing at X-ray wavelengths is necessary. Although these obstacles are by no means unsurmountable, foresight is necessary in order to deliver a functional X-ray lithography process.This work was supported by various agencies, including ARPA/ONR/NRL and the National Science Foundation.

Correlation between Quantitative and Qualitative Analysis on Image Quality of Digital Dental X-ray Images

2012 ◽  
Vol 2 (8) ◽  
pp. 43-51 ◽  
Author(s):  
Siti Arpah Ahmad ◽  
Mohd Nasir Taib ◽  
Noor Elaiza Abdul Khalid ◽  
Haslina Taib
Keyword(s):  
Image Quality ◽  
Qualitative Analysis ◽  
X Ray

Assessment of Some Enhancement Methods of Renal X-ray Image

2020 ◽  
Vol 18 (12) ◽  
pp. 01-05
Author(s):  
Salim J. Attia
Keyword(s):  
Image Quality ◽  
Radiation Dosage ◽  
Histogram Equalization ◽  
Quality Factors ◽  
X Ray ◽  
Adaptive Histogram Equalization ◽  
Quality Image ◽  
Enhancement Method ◽  
Spatial Quality

The study focuses on assessment of the quality of some image enhancement methods which were implemented on renal X-ray images. The enhancement methods included Imadjust, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The images qualities were calculated to compare input images with output images from these three enhancement techniques. An eight renal x-ray images are collected to perform these methods. Generally, the x-ray images are lack of contrast and low in radiation dosage. This lack of image quality can be amended by enhancement process. Three quality image factors were done to assess the resulted images involved (Naturalness Image Quality Evaluator (NIQE), Perception based Image Quality Evaluator (PIQE) and Blind References Image Spatial Quality Evaluator (BRISQE)). The quality of images had been heightened by these methods to support the goals of diagnosis. The results of the chosen enhancement methods of collecting images reflected more qualified images than the original images. According to the results of the quality factors and the assessment of radiology experts, the CLAHE method was the best enhancement method.

In vitro comparison of subjective image quality of the pana digital intraoral x-ray imaging system and conventional intraoral radiography in caries detection

1998 ◽  
Vol 14 (2) ◽  
pp. 75-83 ◽  
Author(s):  
Yoshiko Ariji ◽  
Jin-ichi Takahashi ◽  
Osamu Matsui ◽  
Tsuneichi Okano ◽  
Munetaka Naitoh ◽  
...  
Keyword(s):  
Image Quality ◽  
Imaging System ◽  
Caries Detection ◽  
Intraoral Radiography ◽  
Subjective Image Quality ◽  
X Ray ◽  
X Ray Imaging ◽  
In Vitro Comparison
Sign in / Sign up

Export Citation Format

Share Document