Assessment of segmentation dependence in macroscopic lung cavity extraction

Khdeir A, Geimer T, Chen S, Goppert E, Dankbar M, Bert C, Maier A (2018)

Publication Type: Conference contribution

Publication year: 2018

Journal

Publisher: Springer Berlin Heidelberg

Pages Range: 16-

Conference Proceedings Title: Informatik aktuell

Event location: Erlangen, DEU

DOI: 10.1007/978-3-662-56537-7_14

Abstract

Training of respiratory motion models and population-based patient phantoms of the lung often requires the definition of the entire lung cavity region in the 4D-CT. To ease the workload of clinical experts, automatic selection is highly desirable. Many lung cavity extraction methods rely on a pre-segmented lung volume.

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How to cite

APA:

Khdeir, A., Geimer, T., Chen, S., Goppert, E., Dankbar, M., Bert, C., & Maier, A. (2018). Assessment of segmentation dependence in macroscopic lung cavity extraction. In Heinz Handels, Thomas Tolxdorff, Thomas M. Deserno, Klaus H. Maier-Hein, Andreas Maier, Christoph Palm (Eds.), Informatik aktuell (pp. 16-). Erlangen, DEU: Springer Berlin Heidelberg.

MLA:

Khdeir, Asmaa, et al. "Assessment of segmentation dependence in macroscopic lung cavity extraction." Proceedings of the Workshop on Bildverarbeitung fur die Medizin, 2018, Erlangen, DEU Ed. Heinz Handels, Thomas Tolxdorff, Thomas M. Deserno, Klaus H. Maier-Hein, Andreas Maier, Christoph Palm, Springer Berlin Heidelberg, 2018. 16-.

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