Airway measurement by refinement of synthetic images improves mortality
prediction in idiopathic pulmonary fibrosis
- URL: http://arxiv.org/abs/2208.14141v1
- Date: Tue, 30 Aug 2022 10:48:48 GMT
- Title: Airway measurement by refinement of synthetic images improves mortality
prediction in idiopathic pulmonary fibrosis
- Authors: Ashkan Pakzad, Mou-Cheng Xu, Wing Keung Cheung, Marie Vermant, Tinne
Goos, Laurens J De Sadeleer, Stijn E Verleden, Wim A Wuyts, John R Hurst,
Joseph Jacob
- Abstract summary: We propose synthesising airways by style transfer using perceptual losses to train our model, Airway Transfer Network (ATN)
ATN was shown to be quicker and easier to train than state-of-the-art GAN-based network (simGAN)
ATN-based airway measurements were found to be consistently stronger predictors of mortality than simGAN-derived airway metrics on IPF CTs.
- Score: 1.3290985445255554
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Several chronic lung diseases, like idiopathic pulmonary fibrosis (IPF) are
characterised by abnormal dilatation of the airways. Quantification of airway
features on computed tomography (CT) can help characterise disease progression.
Physics based airway measurement algorithms have been developed, but have met
with limited success in part due to the sheer diversity of airway morphology
seen in clinical practice. Supervised learning methods are also not feasible
due to the high cost of obtaining precise airway annotations. We propose
synthesising airways by style transfer using perceptual losses to train our
model, Airway Transfer Network (ATN). We compare our ATN model with a
state-of-the-art GAN-based network (simGAN) using a) qualitative assessment; b)
assessment of the ability of ATN and simGAN based CT airway metrics to predict
mortality in a population of 113 patients with IPF. ATN was shown to be quicker
and easier to train than simGAN. ATN-based airway measurements were also found
to be consistently stronger predictors of mortality than simGAN-derived airway
metrics on IPF CTs. Airway synthesis by a transformation network that refines
synthetic data using perceptual losses is a realistic alternative to GAN-based
methods for clinical CT analyses of idiopathic pulmonary fibrosis. Our source
code can be found at https://github.com/ashkanpakzad/ATN that is compatible
with the existing open-source airway analysis framework, AirQuant.
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