A Framework for Standardizing Image Quality Assessment in Digital Radiography

Thesis Abstract

Digital radiography has revolutionized diagnostic imaging by providing rapid, high-resolution images; however, significant variability persists in image quality assessment practices across institutions, leading to inconsistent diagnostic outcomes and challenges in ensuring optimal image standards. This study aims to develop a comprehensive, standardized framework for assessing image quality in digital radiography, thereby enhancing reliability, reproducibility, and comparability of imaging assessments across clinical settings. The specific objectives include identifying core image quality parameters, reviewing existing assessment protocols, designing an integrated evaluative model based on these parameters, and validating this model through empirical testing. A mixed-methods research design was employed, integrating qualitative and quantitative approaches. The qualitative component involved a thematic analysis of existing image quality assessment guidelines and expert opinions to identify critical parameters influencing image quality. The quantitative component consisted of a cross-sectional survey of diagnostic radiographers and radiologists working in tertiary hospitals. A total of 150 participants were selected through stratified random sampling from a population of 300 radiography professionals across five major hospitals. Data collection instruments included structured questionnaires, focus group discussions, and standardized image quality evaluation forms. Validity and reliability of these instruments were established through pilot testing and Cronbach’s alpha coefficients exceeding 0.85. Data analysis involved descriptive statistics to delineate current assessment practices and inferential techniques such as factor analysis to identify underlying constructs of image quality. Regression analysis was utilized to examine the relationships between identified parameters and image quality outcomes, and the development of the evaluative framework was guided by the Theory of Perceived Quality and the Signal Detection Theory, which underpin subjective and objective quality assessments. The resulting model proposes a standardized set of criteria and scoring protocols aimed at harmonizing evaluation procedures. Expected findings indicate significant variability in image quality assessment approaches among radiographers, and the study anticipates identifying critical parameters—such as contrast resolution, spatial resolution, noise levels, and display fidelity—that are universally relevant. The research is expected to reveal that a multidimensional evaluation framework incorporating both subjective visual assessments and objective quantifiable metrics improves consistency in image quality determination. The validated framework will be tested further through pilot implementation, demonstrating its utility in clinical decision-making and quality assurance. This study contributes to the existing body of knowledge by offering an empirically validated, universally applicable model for image quality assessment in digital radiography, addressing a critical gap in standardization efforts. It advances theoretical understanding by integrating perceptual and technical evaluation paradigms into a cohesive framework. Practically, the framework serves as a benchmark for radiology departments to standardize inspection protocols, thereby potentially reducing diagnostic errors attributable to variability in image quality assessments. In conclusion, the research underscores the necessity of a harmonized approach to imaging quality evaluation, recommending the adoption of the proposed framework for routine use in radiology units. Further studies are suggested to explore the framework’s applicability across different imaging modalities and digital radiography systems, and to examine its impact on diagnostic accuracy and patient outcomes. Implementation of this standardized assessment protocol promises to elevate quality assurance practices universally, fostering improved clinical standards and patient safety in digital radiography.