Abstract #2465

Are Root Mean Squared Error (RMSE) and Structural Similarity Index (SSIM) the Most Appropriate Metrics for Assessment of MR Image Quality?

Allister Mason^1,2, James Rioux^1,2,3, Sharon Clarke^2,3, Andreu Costa³, Matthias Schmidt³, Valerie Keough³, Thien Huynh³, and Steven Beyea^1,2,3

¹Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada, ²Biomedical Translational Imaging Centre (BIOTIC), Nova Scotia Health Authority, Halifax, NS, Canada, ³Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada

Quantifying MR image quality is important for the evaluation of new image acquisition and reconstruction techniques. Automated objective image quality metrics (IQMs) such as root mean squared error (RMSE) and the structural similarity index (SSIM) are commonly used surrogates for radiologists’ perception of image quality, which can be considered the gold standard. By calculating the correlation between radiologists’ subjective grading and various IQM scores on degraded MR images, we demonstrate that RMSE and SSIM do not correlate as well as other IQMs and are potentially not the most appropriate metrics for assessment of MR image quality.

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