A Realistic Collimated X-Ray Image Simulation Pipeline
El-Zein B, Eckert D, Weber T, Rohleder M, Ritschl L, Kappler S, Maier A (2024)
Publication Type: Conference contribution
Publication year: 2024
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 14379 LNCS
Pages Range: 137-145
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Vancouver, BC
ISBN: 9783031581700
DOI: 10.1007/978-3-031-58171-7_14
Abstract
Collimator detection remains a challenging task in X-ray systems with unreliable or non-available information about the detectors position relative to the source. This paper presents a physically motivated image processing pipeline for simulating the characteristics of collimator shadows in X-ray images. By generating randomized labels for collimator shapes and locations, incorporating scattered radiation simulation, and including Poisson noise, the pipeline enables the expansion of limited datasets for training deep neural networks. We validate the proposed pipeline by a qualitative and quantitative comparison against real collimator shadows. Furthermore, it is demonstrated that utilizing simulated data within our deep learning framework not only serves as a suitable substitute for actual collimators but also enhances the generalization performance when applied to real-world data.
Authors with CRIS profile
Maximilian Rohleder
Lehrstuhl für Informatik 5 (Mustererkennung)
Andreas Maier
Lehrstuhl für Informatik 5 (Mustererkennung)
Involved external institutions
Germany (DE)How to cite
APA:
El-Zein, B., Eckert, D., Weber, T., Rohleder, M., Ritschl, L., Kappler, S., & Maier, A. (2024). A Realistic Collimated X-Ray Image Simulation Pipeline. In Yuan Xue, Chen Chen, Chao Chen, Lianrui Zuo, Yihao Liu (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 137-145). Vancouver, BC, CA: Springer Science and Business Media Deutschland GmbH.
MLA:
El-Zein, Benjamin, et al. "A Realistic Collimated X-Ray Image Simulation Pipeline." Proceedings of the 3rd International Workshop on Data Augmentation, Labeling, and Imperfections, DALI 2023 in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2023, Vancouver, BC Ed. Yuan Xue, Chen Chen, Chao Chen, Lianrui Zuo, Yihao Liu, Springer Science and Business Media Deutschland GmbH, 2024. 137-145.
BibTeX: Download