Font Augmentation: Implant and Surgical Tool Simulation for X-Ray Image Processing

Kordon FJ, Maier A, Swartman B, Kunze H (2020)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2020

Publisher: Springer Vieweg

City/Town: Wiesbaden

Pages Range: 176-182

Conference Proceedings Title: Bildverarbeitung für die Medizin 2020

Event location: Berlin DE

ISBN: 978-3-658

DOI: 10.1007/978-3-658-29267-6_36

Abstract

This study investigates a novel data augmentation approach for simulating surgical instruments, tools, and implants by image composition with transformed characters, numerals, and abstract symbols from open-source fonts. We analyse its suitability for the common spatial learning tasks of multi-label segmentation and anatomical landmark detection. The proposed technique is evaluated on 38 clinical intraoperative X-ray images with a high occurrence of objects overlaying the target anatomy. We demonstrate increased robustness towards superimposed surgical objects by incorporating our technique and provide an empirical rationale about the neglectable influence of realistic object shape and intensity information.


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How to cite

APA:

Kordon, F.J., Maier, A., Swartman, B., & Kunze, H. (2020). Font Augmentation: Implant and Surgical Tool Simulation for X-Ray Image Processing. In Tolxdorff T., Deserno T., Handels H., Maier A., Maier-Hein K., Palm C. (Eds.), Bildverarbeitung für die Medizin 2020 (pp. 176-182). Berlin, DE: Wiesbaden: Springer Vieweg.

MLA:

Kordon, Florian Johannes, et al. "Font Augmentation: Implant and Surgical Tool Simulation for X-Ray Image Processing." Proceedings of the Bildverarbeitung für die Medizin 2020, Berlin Ed. Tolxdorff T., Deserno T., Handels H., Maier A., Maier-Hein K., Palm C., Wiesbaden: Springer Vieweg, 2020. 176-182.

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