Field of View Extension in Computed Tomography Using Deep Learning Prior

Huang Y, Gao L, Preuhs A, Maier A (2020)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2020

Publisher: Springer

Conference Proceedings Title: Bildverarbeitung für die Medizin: Algorithmen – Systeme – Anwendungen

Event location: Berlin DE

URI: https://arxiv.org/abs/1911.01178

DOI: 10.1007/978-3-658-29267-6_40

Abstract

In computed tomography (CT), data truncation is a common problem. Images reconstructed by the standard filtered back-projection algorithm from truncated data suffer from cupping artifacts inside the field-of-view (FOV), while anatomical structures are severely distorted or missing outside the FOV. Deep learning, particularly the U-Net, has been applied to extend the FOV as a post-processing method. Since image-to-image prediction neglects the data fidelity to measured projection data, incorrect structures, even inside the FOV, might be reconstructed by such an approach. Therefore, generating reconstructed images directly from a post-processing neural network is inadequate. In this work, we propose a data consistent reconstruction method, which utilizes deep learning reconstruction as prior for extrapolating truncated projections and a conventional iterative reconstruction to constrain the reconstruction consistent to measured raw data. Its efficacy is demonstrated in our study, achieving small average root-mean-square error of 24 HU inside the FOV and a high structure similarity index of 0.993 for the whole body area on a test patient's CT data.

Authors with CRIS profile

Yixing Huang Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME) Alexander Preuhs Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

How to cite

APA:

Huang, Y., Gao, L., Preuhs, A., & Maier, A. (2020). Field of View Extension in Computed Tomography Using Deep Learning Prior. In Andreas Maier, Klaus Hermann Maier-Hein, Thomas Martin Deserno, Heinz Handels, Thomas Tolxdorff (Eds.), Bildverarbeitung für die Medizin: Algorithmen – Systeme – Anwendungen. Berlin, DE: Springer.

MLA:

Huang, Yixing, et al. "Field of View Extension in Computed Tomography Using Deep Learning Prior." Proceedings of the Bildverarbeitung für die Medizin, Berlin Ed. Andreas Maier, Klaus Hermann Maier-Hein, Thomas Martin Deserno, Heinz Handels, Thomas Tolxdorff, Springer, 2020.

BibTeX: Download