Program Information
An Automated Processing Tool for the Annual Performance Evaluation of An MRI Scanner
K Nkongchu1*, (1) Henry Ford Health System, Detroit, MI
Presentations
MO-F-CAMPUS-IT-2 (Monday, July 31, 2017) 4:30 PM - 5:30 PM Room: Imaging ePoster Theater
Purpose: To implement an automated QC software to evaluate MRI scanner performance via ACR MRI phantom images, B0 homogeneity and its RF coils performances while cutting down on processing time.
Methods: This implementation was broken up into 3 sections: (i) ACR phantom, (ii) RF coils, and (iii) B0 inhomogeneity assessments. Implementation of (i), (ii) & (iii) was done in Matlab via functions which aided in object detection/segmentation of the various inserts in the MRI phantom, and segmentation of image background or objects for noise estimation via the Rayleigh or Rice distribution. The B0 homogeneity estimation, was implemented using the phase difference, phase map and the bandwidth methods. The importation of DICOM images is done via a GUI script which accesses the database of the freeware version of KPacs.
Results: The completed GUI has tools for the displaying & QCing of the results, allowing the user to detect any faulty measurements which could arise from artifacts. Some of these tools are: visualization of ROIs locations on images for evaluation of the RF coils, QCing of the estimated noise via the histogram plots and/or fits for noise estimation using either the Rayleigh or Rice distribution. Verification of automated results via comparison to the manual processing were in good agreement. The verification of the accuracy of the ROIs positions were done by manual windowing of the images which were visually in good agreement. The GUI/software has been tested with DICOM data from scanners manufactured by SIEMENS, Philips, GE and Hitachi. Also included are tools which also allow for manual processing of the data. The processing time for a given scanner is about 90s.
Conclusion: This GUI/software does facilitate evaluation of MRI scanner performance using DICOM images by significantly cutting down on the processing time while aiming to maintain consistency in the QC process.
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