Publication

Synthetic CT generation using focal frequency loss improves image sharpness

Jean-Philippe Thiran
2024

Abstract

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.

Official source

https://infoscience.epfl.ch/entities/publication/fc505704-1cc7-4014-94f1-1a1528b150ee

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Jean-Philippe Thiran
2024

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/fc505704-1cc7-4014-94f1-1a1528b150ee

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Digital image processing is the use of a digital computer to process s through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over . It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.

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