Keywords: Analysis/Processing, Data Processing, synthetic CT
Motivation: Standard intensity-based voxel-wise losses, generally used in image-to-image translation techniques, are typically biased towards the estimation of the low frequency content in image spectra. For the generation of synthetic CT (sCT) contrast, this results in limited image sharpness, and consequently a limited clinical utility.
Goal(s): To improve sharpness in synthetic contrasts.
Approach: We trained a model using a combination of intensity- and frequency-based losses for the generation of sCT images from MRI.
Results: Compared to a baseline model, sCT images generated using the focal-frequency loss resulted in an enhanced level of details in knee images.
Impact: Our results suggest that the use of frequency-based losses, in conjunction with an intensity-based L1 loss, improves image sharpness in synthetic contrasts, and thereby shows the potential to increase their clinical usefulness.
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