Improving Hybrid Quantum Annealing Tomographic Image Reconstruction with Regularization Strategies
Nau M, Vija AH, Reymann M, Gohn W, Maier A (2024)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2024
Publisher: Springer Vieweg
Series: Informatik aktuell
City/Town: Wiesbaden
Pages Range: 3-8
Conference Proceedings Title: Bildverarbeitung für die Medizin 2024. BVM 2024
Event location: Erlangen
ISBN: 9783658440367
DOI: 10.1007/978-3-658-44037-4_3
Abstract
Quantum computing and quantum annealing present promising avenues for addressing complex problems in various fields, including tomographic image reconstruction. This study investigates the application of hybrid quantum annealing in the context of tomographic image reconstruction, focusing on the formulation of compatible conventional image regularization strategies: L2 and total variation. Using a Shepp-Logan phantom of image size 32× 32 with 4-bit grayscale encoding, we study the effect of the regularization techniques under the influence of their parameters and the runtime of the hybrid quantum annealer. The study reveals, that L2 regularization effectively enhances the obtained image reconstructions and total variation can further improve them. Despite efforts to employ regularized hybrid quantum annealing reconstructions, they still fall short in comparison to traditional reconstruction techniques.
Authors with CRIS profile
Merlin Nau
Lehrstuhl für Informatik 5 (Mustererkennung)
Maximilian Reymann
Lehrstuhl für Informatik 5 (Mustererkennung)
Andreas Maier
Lehrstuhl für Informatik 5 (Mustererkennung)
Involved external institutions
United States (USA) (US)How to cite
APA:
Nau, M., Vija, A.H., Reymann, M., Gohn, W., & Maier, A. (2024). Improving Hybrid Quantum Annealing Tomographic Image Reconstruction with Regularization Strategies. In Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024. BVM 2024 (pp. 3-8). Erlangen, DE: Wiesbaden: Springer Vieweg.
MLA:
Nau, Merlin, et al. "Improving Hybrid Quantum Annealing Tomographic Image Reconstruction with Regularization Strategies." Proceedings of the German Conference on Medical Image Computing - Bildverarbeitung für die Medizin, Erlangen Ed. Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff, Wiesbaden: Springer Vieweg, 2024. 3-8.
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