Instance Segmentation XXL-CT Challenge of a Historic Airplane

Gruber R, Engster JC, Michen M, Blum N, Stille M, Gerth S, Wittenberg T (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Journal of Nondestructive Evaluation Springer Verlag (Germany)

Book Volume: 44

Article Number: 1

Journal Issue: 1

DOI: 10.1007/s10921-024-01136-y

Abstract

Instance segmentation of compound objects in XXL-CT imagery poses a unique challenge in non-destructive testing. This complexity arises from the lack of known reference segmentation labels, limited applicable segmentation tools, as well as partially degraded image quality. To asses recent advancements in the field of machine learning-based image segmentation, the ‘Instance Segmentation XXL-CT Challenge of a Historic Airplane’ was conducted. The challenge aimed to explore automatic or interactive instance segmentation methods for an efficient delineation of the different aircraft components, such as screws, rivets, metal sheets or pressure tubes. We report the organization and outcome of this challenge and describe the capabilities and limitations of the submitted segmentation methods.

Authors with CRIS profile

Thomas Wittenberg

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE) Fraunhofer-Einrichtung für Individualisierte und Zellbasierte Medizintechnik / Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering (IMTE) DE Germany (DE)

How to cite

APA:

Gruber, R., Engster, J.C., Michen, M., Blum, N., Stille, M., Gerth, S., & Wittenberg, T. (2025). Instance Segmentation XXL-CT Challenge of a Historic Airplane. Journal of Nondestructive Evaluation, 44(1). https://doi.org/10.1007/s10921-024-01136-y

MLA:

Gruber, Roland, et al. "Instance Segmentation XXL-CT Challenge of a Historic Airplane." Journal of Nondestructive Evaluation 44.1 (2025).

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