Abstract #3310

Super resolution permits fast, low resolution bSSFP imaging of the temporal bone…but do radiologists agree on image quality?

Sarah Reeve^1,2, Alessandro Guida^2,3, Chris Bowen^1,2,3, James Rioux^1,2,3, David Volders^3,4, Jens Heidenreich^3,4, and Steven Beyea^1,3,5,6

¹Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada, ²Biomedical Translational Imaging Centre, QEII Health Sciences Centre, Halifax, NS, Canada, ³Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada, ⁴Diagnostic Imaging, QEII Health Sciences Centre, Halifax, NS, Canada, ⁵Biomedical Translational Imaging Centre, IWK Health Centre, Halifax, NS, Canada, ⁶School of Biomedical Engineering, Dalhousie University, Halifax, NS, Canada

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Head & Neck/ENT, Super ResolutionLow resolution (LR) balanced steady-state free precession (bSSFP) acquisitions confer decreased acquisition times, reduced patient motion and heating, and increased artifact tolerance due to a decrease in TR. The application of a pre-trained super resolution network to LR bSSFP images of the temporal bone allows for these advantages to be realized, without significantly degrading image quality. In the absence of a matched high resolution image, quality was judged by two radiologists. However, radiologist’s ratings were not in agreement, highlighting the fact that there is no single definition of task-specific image quality, which must be considered when super resolution is performed.

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