Processor quality control in laser imaging systems

Bogucki, Terese M.; Murphy, W. R.; Baker, Carol S.; Piazza, S. S.; Haus, Arthur G.

doi:10.1118/1.597940

Cited by 9 publications

(6 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Care must be taken to accurately convert the optical density to dose from a film measurement. 72,[77][78][79] Commissioning of each film batch should include characterizing the dose response, sensitivity, and uniformity of the film. The amount of noise in the film should be considered when determining the dose to be delivered to the film.…”

Section: B 2d Methodsmentioning

confidence: 99%

“…Both radiographic (e.g., EDR2) and radiochromic (e.g., EBT2) films have been used. Care must be taken to accurately convert the optical density to dose from a film measurement . Commissioning of each film batch should include characterizing the dose response, sensitivity, and uniformity of the film.…”

Section: Review Of Methodologies For Absolute Dose Verificationmentioning

confidence: 99%

See 1 more Smart Citation

Tolerance limits and methodologies forIMRTmeasurement‐based verificationQA:Recommendations ofAAPMTask Group No. 218

et al. 2018

View full text Add to dashboard Cite

Purpose: Patient-specific IMRT QA measurements are important components of processes designed to identify discrepancies between calculated and delivered radiation doses. Discrepancy tolerance limits are neither well defined nor consistently applied across centers. The AAPM TG-218 report provides a comprehensive review aimed at improving the understanding and consistency of these processes as well as recommendations for methodologies and tolerance limits in patient-specific IMRT QA. Methods: The performance of the dose difference/distance-to-agreement (DTA) and c dose distribution comparison metrics are investigated. Measurement methods are reviewed and followed by a discussion of the pros and cons of each. Methodologies for absolute dose verification are discussed and new IMRT QA verification tools are presented. Literature on the expected or achievable agreement between measurements and calculations for different types of planning and delivery systems are reviewed and analyzed. Tests of vendor implementations of the c verification algorithm employing benchmark cases are presented. Results: Operational shortcomings that can reduce the c tool accuracy and subsequent effectiveness for IMRT QA are described. Practical considerations including spatial resolution, normalization, dose threshold, and data interpretation are discussed. Published data on IMRT QA and the clinical experience of the group members are used to develop guidelines and recommendations on tolerance and action limits for IMRT QA. Steps to check failed IMRT QA plans are outlined. Conclusion: Recommendations on delivery methods, data interpretation, dose normalization, the use of c analysis routines and choice of tolerance limits for IMRT QA are made with focus on detecting differences between calculated and measured doses via the use of robust analysis methods and an in-depth understanding of IMRT verification metrics. The recommendations are intended to improve the IMRT QA process and establish consistent, and comparable IMRT QA criteria among institutions.

show abstract

Section: B 2d Methodsmentioning

confidence: 99%

Section: Review Of Methodologies For Absolute Dose Verificationmentioning

confidence: 99%

Tolerance limits and methodologies forIMRTmeasurement‐based verificationQA:Recommendations ofAAPMTask Group No. 218

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Also, it is convex fuzzy 1]. Similarly, the abnormal class (ω 2 ) can be defined byÃ γ (v) = {v : µÃ(v) < γ}.…”

Section: Fuzzy Random Variables For Monitoring Quality Fearuresmentioning

confidence: 99%

“…Also, the processing time, solution temperature, and chemical replenishment are controlled through sensing device and processor. Considering the complexity, uncertainty, and the vitality of imaging diagnosis in today's health care, the requirement for an effective process control becomes even more important [1,12]. For example, Baek and Park (2008) proposed correction algorithm that can correct the distorted medical image during scanning.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy intelligent quality monitoring model for X-ray image processing

Khalatbari

Jenab

2009

Journal of X-Ray Science and Technology

View full text Add to dashboard Cite

Today's imaging diagnosis needs to adapt modern techniques of quality engineering to maintain and improve its accuracy and reliability in health care system. One of the main factors that influences diagnostic accuracy of plain film X-ray on detecting pathology is the level of film exposure. If the level of film exposure is not adequate, a normal body structure may be interpretated as pathology and vice versa. This not only influences the patient management but also has an impact on health care cost and patient's quality of life. Therefore, providing an accurate and high quality image is the first step toward an excellent patient management in any health care system. In this paper, we study these techniques and also present a fuzzy intelligent quality monitoring model, which can be used to keep variables from degrading the image quality. The variables derived from chemical activity, cleaning procedures, maintenance, and monitoring may not be sensed, measured, or calculated precisely due to uncertain situations. Therefore, the γ-level fuzzy Bayesian model for quality monitoring of an image processing is proposed. In order to apply the Bayesian concept, the fuzzy quality characteristics are assumed as fuzzy random variables. Using the fuzzy quality characteristics, the newly developed model calculates the degradation risk for image processing. A numerical example is also presented to demonstrate the application of the model.

show abstract

“…These include variations in film sensitivity caused by film batch, processor conditions, variations in photon beam spectrum throughout the measured dose distribution, and densitometry artifacts. Of these variables, the one that has the greatest potential for causing dosimetry errors is the variation in optical density ͑OD͒ with film processor developer temperature ͑TG 69 and Bogucki et al 94 ͒. When considering the trade-off between experimental complexity and labor and the information obtained, radiographic film provides an attractive measurement technique.…”

Section: Iib1 Filmmentioning

confidence: 99%

Dosimetry tools and techniques for IMRT

et al. 2011

View full text Add to dashboard Cite

Intensity modulated radiation therapy ͑IMRT͒ poses a number of challenges for properly measuring commissioning data and quality assurance ͑QA͒ radiation dose distributions. This report provides a comprehensive overview of how dosimeters, phantoms, and dose distribution analysis techniques should be used to support the commissioning and quality assurance requirements of an IMRT program. The proper applications of each dosimeter are described along with the limitations of each system. Point detectors, arrays, film, and electronic portal imagers are discussed with respect to their proper use, along with potential applications of 3D dosimetry. Regardless of the IMRT technique utilized, some situations require the use of multiple detectors for the acquisition of accurate commissioning data. The overall goal of this task group report is to provide a document that aids the physicist in the proper selection and use of the dosimetry tools available for IMRT QA and to provide a resource for physicists that describes dosimetry measurement techniques for purposes of IMRT commissioning and measurement-based characterization or verification of IMRT treatment plans. This report is not intended to provide a comprehensive review of commissioning and QA procedures for IMRT. Instead, this report focuses on the aspects of metrology, particularly the practical aspects of measurements that are unique to IMRT. The metrology of IMRT concerns the application of measurement instruments and their suitability, calibration, and quality control of measurements. Each of the dosimetry measurement tools has limitations that need to be considered when incorporating them into a commissioning process or a comprehensive QA program. For example, routine quality assurance procedures require the use of robust field dosimetry systems. These often exhibit limitations with respect to spatial resolution or energy response and need to themselves be commissioned against more established dosimeters. A chain of dosimeters, from secondary standards to field instruments, is established to assure the quantitative nature of the tests. This report is intended to describe the characteristics of the components of these systems; dosimeters, phantoms, and dose evaluation algorithms. This work is the report of AAPM Task Group 120.

show abstract

Processor quality control in laser imaging systems

Cited by 9 publications

References 2 publications

Tolerance limits and methodologies forIMRTmeasurement‐based verificationQA:Recommendations ofAAPMTask Group No. 218

Tolerance limits and methodologies forIMRTmeasurement‐based verificationQA:Recommendations ofAAPMTask Group No. 218

Fuzzy intelligent quality monitoring model for X-ray image processing

Dosimetry tools and techniques for IMRT

Contact Info

Product

Resources

About