Handling Label Uncertainty on the Example of Automatic Detection of Shepherd’s Crook RCA in Coronary CT Angiography

Denzinger F, Wels M, Taubmann O, Kordon F, Wagner F, Mehltretter S, Gülsün MA, Schöbinger M, André F, Buß SJ, Görich J, Sühling M, Maier A, Breininger K (2023)

Publication Type: Conference contribution

Publication year: 2023

Publisher: IEEE

Book Volume: 2023-April

Conference Proceedings Title: Proceedings - International Symposium on Biomedical Imaging

Event location: Cartagena

ISBN: 9781665473583

DOI: 10.1109/ISBI53787.2023.10230565

Abstract

Coronary artery disease (CAD) is often treated minimally invasively with a catheter being inserted into the diseased coronary vessel. If a patient exhibits a Shepherd’s Crook (SC) Right Coronary Artery (RCA) – an anatomical norm variant of the coronary vasculature – the complexity of this procedure is increased. Automated reporting of this variant from coronary CT angiography screening would ease prior risk assessment. We propose a 1D convolutional neural network which leverages a sequence of residual dilated convolutions to automatically determine this norm variant from a prior extracted vessel centerline. As the SC RCA is not clearly defined with respect to concrete measurements, labeling also includes qualitative aspects. Therefore, 4.23 % samples in our dataset of 519 RCA centerlines were labeled as unsure SC RCAs, with 5.97 % being labeled as sure SC RCAs. We explore measures to handle this label uncertainty, namely global/model-wise random assignment, exclusion, and soft label assignment. Furthermore, we evaluate how this uncertainty can be leveraged for the determination of a rejection class. With our best configuration, we reach an area under the receiver operating characteristic curve (AUC) of 0.938 on confident labels. Moreover, we observe an increase of up to 0.020 AUC when rejecting 10 % of the data and leveraging the labeling uncertainty information in the exclusion process.

Authors with CRIS profile

Involved external institutions

Siemens AG, Healthcare Sector Germany (DE) Das Radiologische Zentrum (MVZ-DRZ) Germany (DE) Siemens Healthineers Germany (DE)

How to cite

APA:

Denzinger, F., Wels, M., Taubmann, O., Kordon, F., Wagner, F., Mehltretter, S.,... Breininger, K. (2023). Handling Label Uncertainty on the Example of Automatic Detection of Shepherd’s Crook RCA in Coronary CT Angiography. In Proceedings - International Symposium on Biomedical Imaging. Cartagena, CO: IEEE.

MLA:

Denzinger, Felix, et al. "Handling Label Uncertainty on the Example of Automatic Detection of Shepherd’s Crook RCA in Coronary CT Angiography." Proceedings of the 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), Cartagena IEEE, 2023.

BibTeX: Download