Rohleder M, Pradel C, Wagner F, Thies M, Maul N, Denzinger F, Maier A, Kreher B (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 14222 LNCS
Pages Range: 57-65
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Vancouver, BC, CAN
ISBN: 9783031438974
DOI: 10.1007/978-3-031-43898-1_6
Epipolar geometry is exploited in several applications in the field of Cone-Beam Computed Tomography (CBCT) imaging. By leveraging consistency conditions between multiple views of the same scene, motion artifacts can be minimized, the effects of beam hardening can be reduced, and segmentation masks can be refined. In this work, we explore the idea of enabling deep learning models to access the known geometrical relations between views. This implicit 3D information can potentially enhance various projection domain algorithms such as segmentation, detection, or inpainting. We introduce a differentiable feature translation operator, which uses available projection matrices to calculate and integrate over the epipolar line in a second view. As an example application, we evaluate the effects of the operator on the task of projection domain metal segmentation. By re-sampling a stack of projections into orthogonal view pairs, we segment each projection image jointly with a second view acquired roughly 90 $$^\circ $$ apart. The comparison with an equivalent single-view segmentation model reveals an improved segmentation performance of 0.95 over 0.91 measured by the dice coefficient. By providing an implementation of this operator as an open-access differentiable layer, we seek to enable future research.
APA:
Rohleder, M., Pradel, C., Wagner, F., Thies, M., Maul, N., Denzinger, F.,... Kreher, B. (2023). Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation. In Hayit Greenspan, Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 57-65). Vancouver, BC, CAN: Springer Science and Business Media Deutschland GmbH.
MLA:
Rohleder, Maximilian, et al. "Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation." Proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, Vancouver, BC, CAN Ed. Hayit Greenspan, Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor, Springer Science and Business Media Deutschland GmbH, 2023. 57-65.
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