Ines Ben Alaya* and Mokhtar Mars Pages 1 - 10 ( 10 )
Background: Quality Assurance (QA) of Magnetic Resonance Imaging (MRI) systems is an essential step to avoid problems in diagnosis when image quality is low. It considered as a patient safety issue. The accreditation program of the American College of Radiology (ACR) includes a standardized image quality measurement protocol. However, it has been shown that human testing by visual inspection is not objective and not reproducible.
Methods: Thereby, the overall goal of the present paper was to develop and implement a fully automated method for accurate image analysis to increase its objectivity. It can positively impact the QA process by decreasing reaction time, improving repeatability, and by reducing operator dependency. The proposed QA procedures were applied to ten clinical MRI scanners. The performance of the automated procedure was assessed by comparing the test results with the decisions made by trained MRI technologists according to ACR guidelines. We, also, computed the p-value and correlation coefficient of the manual and automatic measurements using the Pearson test.
Result and Conclusion: Compared to the manual process, the use of the proposed approach can significantly reduce the time requirements while maintaining consistency with manual measurements and furthermore decrease the subjectivity of the results. Accordingly, a strong correlation was found and the corresponding p-value was much lower than the significance level of 0.05 indicating good agreement between the two measurements.
Magnetic Resonance Imaging , Quality control , ACR MRI phantom , MRI image quality , Image processing.
Laboratory of Biophysics and Medical Technology, Higher Institute of Medical Technology of Tunis, Tunis El Manar University, 1006 Tunis, Laboratory of Biophysics and Medical Technology, Higher Institute of Medical Technology of Tunis, Tunis El Manar University, 1006 Tunis