Segmentation of Acute Ischemic Stroke in Native and Enhanced CT using Uncertainty-aware Labels

Vorberg L, Taubmann O, Ditt H, Maier A (2024)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2024

Journal

Informatik aktuell Gesellschaft für Informatik (GI)

Publisher: Springer Vieweg

Series: Informatik aktuell

City/Town: Wiesbaden

Pages Range: 267-272

Conference Proceedings Title: Bildverarbeitung für die Medizin 2024. BVM 2024

Event location: Erlangen DE

ISBN: 9783658440367

DOI: 10.1007/978-3-658-44037-4_72

Abstract

In stroke diagnosis, a non-contrast CT (NCCT) is the first scan acquired and bears the possibility to identify ischemic changes in the brain. Their identification and segmentation are subject to high inter-rater variability. We develop and evaluate models based on labels that reflect the uncertainty in segmentation hypotheses by annotation of minimum (“inner”) and maximum (“outer”) contours of perceived presence of infarct core and hypoperfused tissue. These labels are used for training nnU-Net to segment both from NCCT and CT angiography (CTA) scans of 167 patients. The predicted output is post-processed to obtain delineations of the tissue of interest at varying distances between inner and outer contours. Compared to the ground truth, infarcts of medium size (10 to 70 ml) could be segmented in the NCCT scans with a median error of 3.7 ml (6.2 ml for CTA) of excess predicted volume, missing 6.4 ml (3.5 ml) of the infarct.

Authors with CRIS profile

Linda Vorberg Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

How to cite

APA:

Vorberg, L., Taubmann, O., Ditt, H., & Maier, A. (2024). Segmentation of Acute Ischemic Stroke in Native and Enhanced CT using Uncertainty-aware Labels. In Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024. BVM 2024 (pp. 267-272). Erlangen, DE: Wiesbaden: Springer Vieweg.

MLA:

Vorberg, Linda, et al. "Segmentation of Acute Ischemic Stroke in Native and Enhanced CT using Uncertainty-aware Labels." Proceedings of the German Conference on Medical Image Computing, BVM 2024, Erlangen Ed. Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff, Wiesbaden: Springer Vieweg, 2024. 267-272.

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