Deep Iterative 2D/3D Registration

Jaganathan S, Wang J, Borsdorf A, Shetty K, Maier A (2021)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2021

Journal

Lecture Notes in Computer Science Springer Verlag

Original Authors: Srikrishna Jaganathan, Jian Wang, Anja Borsdorf, Karthik Shetty, Andreas Maier

Publisher: Springer Nature

Pages Range: 383-392

Conference Proceedings Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

Event location: Strasbourg FR

DOI: 10.1007/978-3-030-87202-1_37

Abstract

Deep Learning-based 2D/3D registration methods are highly robust but often lack the necessary registration accuracy for clinical application. A refinement step using the classical optimization-based 2D/3D registration method applied in combination with Deep Learning-based techniques can provide the required accuracy. However, it also increases the runtime. In this work, we propose a novel Deep Learning driven 2D/3D registration framework that can be used end-to-end for iterative registration tasks without relying on any further refinement step. We accomplish this by learning the update step of the 2D/3D registration framework using Point-to-Plane Correspondences. The update step is learned using iterative residual refinement-based optical flow estimation, in combination with the Point-to-Plane correspondence solver embedded as a known operator. Our proposed method achieves an average runtime of around 8s, a mean re-projection distance error of 0.60±0.40 mm with a success ratio of 97% and a capture range of 60 mm. The combination of high registration accuracy, high robustness, and fast runtime makes our solution ideal for clinical applications.

Authors with CRIS profile

Srikrishna Jaganathan Lehrstuhl für Informatik 5 (Mustererkennung) Karthik Shetty Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Involved external institutions

Siemens Healthineers DE Germany (DE)

How to cite

APA:

Jaganathan, S., Wang, J., Borsdorf, A., Shetty, K., & Maier, A. (2021). Deep Iterative 2D/3D Registration. In Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 (pp. 383-392). Strasbourg, FR: Springer Nature.

MLA:

Jaganathan, Srikrishna, et al. "Deep Iterative 2D/3D Registration." Proceedings of the MICCAI 2021 - 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, Strasbourg Ed. Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert, Springer Nature, 2021. 383-392.

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