Multi-Modal Super-Resolution with Deep Guided Filtering
Stimpel B, Syben-Leisner C, Schirrmacher F, Dörfler A, Maier A, Hölter P (2019)
Publication Type: Conference contribution
Publication year: 2019
Journal
Publisher: Springer Berlin Heidelberg
Pages Range: 110-115
Conference Proceedings Title: Informatik aktuell
Event location: Lübeck
ISBN: 9783658253257
DOI: 10.1007/978-3-658-25326-4_25
Abstract
Despite the visually appealing results, most Deep Learningbased super-resolution approaches lack the comprehensibility that is required for medical applications. We propose a modified version of the locally linear guided filter for the application of super-resolution in medical imaging. The guidance map itself is learned end-to-end from multimodal inputs, while the actual data is only processed with known operators. This ensures comprehensibility of the results and simplifies the implementation of guarantees. We demonstrate the possibilities of our approach based on multi-modal MR and cross-modal CT and MR data. For both datasets, our approach performs clearly better than bicubic upsampling. For projection images, we achieve SSIMs of up to 0.99, while slice image data results in SSIMs of up to 0.98 for four-fold upsampling given an image of the respective other modality at full resolution. In addition, end-to-end learning of the guidance map considerably improves the quality of the results.
Authors with CRIS profile
Bernhard Stimpel
Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung)
Christopher Syben
Lehrstuhl für Informatik 5 (Mustererkennung)
Franziska Schirrmacher
Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung)
Arnd Dörfler
Department of Neuroradiology
Andreas Maier
Lehrstuhl für Informatik 5 (Mustererkennung)
Philip Hölter
Department of Neuroradiology
How to cite
APA:
Stimpel, B., Syben-Leisner, C., Schirrmacher, F., Dörfler, A., Maier, A., & Hölter, P. (2019). Multi-Modal Super-Resolution with Deep Guided Filtering. In Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 110-115). Lübeck, DE: Springer Berlin Heidelberg.
MLA:
Stimpel, Bernhard, et al. "Multi-Modal Super-Resolution with Deep Guided Filtering." Proceedings of the Workshop on Bildverarbeitung fur die Medizin, 2019, Lübeck Ed. Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff, Springer Berlin Heidelberg, 2019. 110-115.
BibTeX: Download