Diagnostic radiology equipment

2015 ◽  
Author(s):  
Jerry R Williams
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Image Quality ◽  
Radiation Protection ◽  
Image Quality Assessment ◽  
Dose Assessment ◽  
Detector Efficiency ◽  
Dose Saving ◽  
Working Practices ◽  
Safe Working

The chapter is concerned with the features of radiographic and fluoroscopic equipment that present radiation protection issues for both patients and staff. These are managed through regulation, manufacturing standards, and adherence to safe working practices. It is different for patients who are deliberately irradiated in accordance with justification protocols not considered here. Radiation protection is based on the ALARP principle which requires the resultant dose to be minimized consistent with image quality is sufficient to provide accurate and safe diagnosis. Dose minimization is critically dependent on detector efficiency. Quality control of dose for individual examinations is particularly important to provide assurance of ALARP. It should include not only patient dose assessment but also detector dose indicators, particularly in radiography. These issues are discussed in detail together with other dose-saving features and discussion on objective methods of image quality assessment. Commissioning and lifetime tests are required for quality assurance programmes. These are described.

scholarly journals Establishing a quality assurance baseline for radiological protection of patients undergoing diagnostic radiology

2011 ◽  
Vol 15 (3) ◽  
pp. 70 ◽  
Author(s):  
Geoffrey K Korir ◽  
Jeska Sidika Wambani ◽  
Ian K Korir
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Image Quality ◽  
Radiation Exposure ◽  
High Speed ◽  
Quality Criteria ◽  
Patient Dose ◽  
Radiological Protection ◽  
X Ray ◽  
High Speed Film

Background. The wide use of ionising radiation in medical care has resulted in the largest man-made cause of radiation exposure. In recent years, diagnostic departments in Kenya have adapted the high-speed film/screen combination without well-established quality control, objective image quality criteria, and assessment of patient dose. The safety of patients in terms of justification and the as-low-as-reasonably-achievable (ALARA) principle is inadequate without quality assurance measures. Aim. This study assessed the level of film rejects, device performance, image quality and patient dose in 4 representative hospitals using high-speed film/screen combination. Results. The X-ray equipment quality control tests performance range was 67% to 90%, and 63% of the radiographs were of good diagnostic value. The measured prevalent chest examination entrance surface dose (ESD) showed levels above the international diagnostic reference levels (DRLs), while lumbar spine and pelvis examination was the largest source of radiation exposure to patients. Conclusion. The optimisation of patient protection can be achieved with optimally performing X-ray equipment, the application of good radiographic technique, and continuous assessment of radiographic image quality.

SEM image quality assessment for mask quality control

2021 ◽  
Author(s):  
Nivea G. Schuch ◽  
Alexandre Moly ◽  
Charles Valade ◽  
Nassim Halli ◽  
Mohamed Abaidi ◽  
...  
Keyword(s):  
Quality Control ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Sem Image

scholarly journals Automated daily quality control analysis for mammography in a multi-unit imaging center

2018 ◽  
Vol 60 (2) ◽  
pp. 140-148
Author(s):  
Veli-Matti Sundell ◽  
Teemu Mäkelä ◽  
Alexander Meaney ◽  
Touko Kaasalainen ◽  
Sauli Savolainen
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Image Quality ◽  
Digital Mammography ◽  
Visual Analysis ◽  
Quality Analysis ◽  
Analysis Software ◽  
Image Quality Analysis ◽  
Imaging Center

Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

scholarly journals Proposals for the Russian quality assurance program in computed tomography

2021 ◽  
Vol 14 (1) ◽  
pp. 17-33
Author(s):  
P. S. Druzhinina ◽  
L. A. Chipiga ◽  
S. A. Ryzhov ◽  
A. V. Vodovatov ◽  
G. V. Berkovich ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Quality Control ◽  
Quality Assurance ◽  
Radiation Protection ◽  
Quality Assurance Program ◽  
Control Optimization ◽  
Image Quality Control ◽  
Patient Doses ◽  
Exposure Levels ◽  
Ct Image Quality

To ensure the quality assurance of CT-examinations, it is necessary to obtain the high-quality diagnostic information and maintain the optimal exposure levels of patients and medical staff. This paper is focused on the requirements and main aspects of quality assurance of CT-examinations, which include quality control of the equipment, methods of CT-image quality control, optimization of radiation protection, as well as management of the unintended and accidental medical exposure. The paper contains recommendations on quality control of diagnostic equipment, methods for monitoring the quality control of CT-images, values of diagnostic reference levels for the detection of abnormally high patient doses and optimization of the radiation protection of patients, as well as the recommendations for management of radiation and non-radiation accidents. All main sections of the paper represent an unified quality assurance system in computed tomography.

A Novel Hybrid Image Quality Assessment Algorithm

2011 ◽  
Vol 4 (4) ◽  
pp. 107-108
Author(s):  
Deepa Maria Thomas ◽  
◽  
S. John Livingston
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment

Document Image Quality Assessment with Relaying Reference to Determine Minimum Readable Resolution for Compression

2020 ◽  
Vol 2020 (9) ◽  
pp. 323-1-323-8
Author(s):  
Litao Hu ◽  
Zhenhua Hu ◽  
Peter Bauer ◽  
Todd J. Harris ◽  
Jan P. Allebach
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Research Area ◽  
Input Image ◽  
Quality Score ◽  
Document Image ◽  
Digital Cameras ◽  
Active Research ◽  
Traditional Approaches

Image quality assessment has been a very active research area in the field of image processing, and there have been numerous methods proposed. However, most of the existing methods focus on digital images that only or mainly contain pictures or photos taken by digital cameras. Traditional approaches evaluate an input image as a whole and try to estimate a quality score for the image, in order to give viewers an idea of how “good” the image looks. In this paper, we mainly focus on the quality evaluation of contents of symbols like texts, bar-codes, QR-codes, lines, and hand-writings in target images. Estimating a quality score for this kind of information can be based on whether or not it is readable by a human, or recognizable by a decoder. Moreover, we mainly study the viewing quality of the scanned document of a printed image. For this purpose, we propose a novel image quality assessment algorithm that is able to determine the readability of a scanned document or regions in a scanned document. Experimental results on some testing images demonstrate the effectiveness of our method.

No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics

2020 ◽  
Vol 64 (1) ◽  
pp. 10505-1-10505-16
Author(s):  
Yin Zhang ◽  
Xuehan Bai ◽  
Junhua Yan ◽  
Yongqi Xiao ◽  
C. R. Chatwin ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Image Distortion ◽  
Image Feature ◽  
Reference Image ◽  
Gradient Magnitude ◽  
Distortion Type

Abstract A new blind image quality assessment method called No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics is proposed, which is aimed at solving the problem that the existing no-reference image quality assessment methods cannot determine the type of image distortion and that the quality evaluation has poor robustness for different types of distortion. In this article, an 18-dimensional image feature vector is constructed from gradient magnitude features, relative gradient orientation features, and relative gradient magnitude features over two scales and three orders on the basis of the relationship between multi-order gradient statistics and the type and degree of image distortion. The feature matrix and distortion types of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion type; the feature matrix and subjective scores of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion degree. A series of comparative experiments were carried out using Laboratory of Image and Video Engineering (LIVE), LIVE Multiply Distorted Image Quality, Tampere Image, and Optics Remote Sensing Image databases. Experimental results show that the proposed method has high distortion type judgment accuracy and that the quality score shows good subjective consistency and robustness for all types of distortion. The performance of the proposed method is not constricted to a particular database, and the proposed method has high operational efficiency.

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