Improving 3D image quality of x-ray C-arm imaging systems by using properly designed pose determination systems for calibrating the projection geometry

Author(s):  
Norbert K. Strobel ◽  
Benno Heigl ◽  
Thomas M. Brunner ◽  
Oliver Schuetz ◽  
Matthias M. Mitschke ◽  
...  
Author(s):  
Jack L. Glover ◽  
Praful Gupta ◽  
Nicholas G. Paulter Jr. ◽  
Alan C. Bovik

Portable X-ray imaging systems are routinely used by bomb squads throughout the world to image the contents of suspicious packages and explosive devices. The images are used by bomb technicians to determine whether or not packages contain explosive devices or device components. In events of positive detection, the images are also used to understand device design and to devise countermeasures. The quality of the images is considered to be of primary importance by users and manufacturers of these systems, since it affects the ability of the users to analyze the images and to detect potential threats. As such, there exist national standards that set minimum acceptable image-quality levels for the performance of these imaging systems. An implicit assumption is that better image quality leads to better user identification of components in explosive devices and, therefore, better informed plans to render them safe. However, there is no previously published experimental work investigating this. Toward advancing progress in this direction, the authors developed the new NIST-LIVE X-ray improvised explosive device (IED) image-quality database. The database consists of: a set of pristine X-ray images of IEDs and benign objects; a larger set of distorted images of varying quality of the same objects; ground-truth IED component labels for all images; and human task-performance results locating and identifying the IED components. More than 40 trained U.S. bomb technicians were recruited to generate the human task-performance data. They use the database to show that identification probabilities for IED components are strongly correlated with image quality. They also show how the results relate to the image-quality metrics described in the current U.S. national standard for these systems, and how their results can be used to inform the development of baseline performance requirements. They expect these results to directly affect future revisions of the standard.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Karen Panetta ◽  
Arash Samani ◽  
Sos Agaian

Medical imaging systems often require image enhancement, such as improving the image contrast, to provide medical professionals with the best visual image quality. This helps in anomaly detection and diagnosis. Most enhancement algorithms are iterative processes that require many parameters be selected. Poor or nonoptimal parameter selection can have a negative effect on the enhancement process. In this paper, a quantitative metric for measuring the image quality is used to select the optimal operating parameters for the enhancement algorithms. A variety of measures evaluating the quality of an image enhancement will be presented along with each measure’s basis for analysis, namely, on image content and image attributes. We also provide guidelines for systematically choosing the proper measure of image quality for medical images.


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

1993 ◽  
Vol 306 ◽  
Author(s):  
F. Cerrina ◽  
G.M. Wells

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.


2012 ◽  
Vol 2 (8) ◽  
pp. 43-51 ◽  
Author(s):  
Siti Arpah Ahmad ◽  
Mohd Nasir Taib ◽  
Noor Elaiza Abdul Khalid ◽  
Haslina Taib

2020 ◽  
Vol 18 (12) ◽  
pp. 01-05
Author(s):  
Salim J. Attia

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.


1998 ◽  
Vol 14 (2) ◽  
pp. 75-83 ◽  
Author(s):  
Yoshiko Ariji ◽  
Jin-ichi Takahashi ◽  
Osamu Matsui ◽  
Tsuneichi Okano ◽  
Munetaka Naitoh ◽  
...  

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