An active learning approach for the interactive and guided segmentation of tomography data

Bashir Kazimi; Philipp Heuser; Frank Schluenzen; Hanna Cwieka; Diana Krüger; Berit Zeller-Plumhoff; Florian Wieland; Jörg U. Hammel; Felix Beckmann; Julian Moosmann

doi:10.1117/12.2637973

10 November 2022 An active learning approach for the interactive and guided segmentation of tomography data

Bashir Kazimi, Philipp Heuser, Frank Schluenzen, Hanna Cwieka, Diana Krüger, Berit Zeller-Plumhoff, Florian Wieland, Jörg U. Hammel, Felix Beckmann, Julian Moosmann

Author Affiliations +

Proceedings Volume 12242, Developments in X-Ray Tomography XIV; 122420F (2022) https://doi.org/10.1117/12.2637973
Event: SPIE Optical Engineering + Applications, 2022, San Diego, California, United States

Abstract

The Helmholtz-Zentrum Hereon is operating several tomography end stations at the beamlines P05 and P07 of the synchrotron radiation facility PETRA III at DESY in Hamburg, Germany. Attenuation and phase contrast imaging techniques are provided as well as sample environments for in situ/operando/vivo experiments for applications in biology, medicine, materials science, etc. Very large and diverse data sets with varying spatiotemporal resolution, noise levels and artifacts are acquired which are challenging to process and analyze. Here we report on an active learning approach for the semantic segmentation of tomography data using a guided and interactive framework, and evaluate different acquisition functions for the selection of images to be annotated in the iterative process.

Conference Presentation

Citation Download Citation

Bashir Kazimi, Philipp Heuser, Frank Schluenzen, Hanna Cwieka, Diana Krüger, Berit Zeller-Plumhoff, Florian Wieland, Jörg U. Hammel, Felix Beckmann, and Julian Moosmann "An active learning approach for the interactive and guided segmentation of tomography data", Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122420F (10 November 2022); https://doi.org/10.1117/12.2637973

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