Segmentation of Peripancreatic Arteries in Multispectral Computed Tomography Imaging
Dima A, Paetzold JC, Jungmann F, Lemke T, Raffler P, Kaissis G, Rueckert D, Braren R (2021)
Publication Type: Conference contribution
Publication year: 2021
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12966 LNCS
Pages Range: 596-605
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Virtual, Online
ISBN: 9783030875886
DOI: 10.1007/978-3-030-87589-3_61
Abstract
Pancreatic ductal adenocarcinoma is an aggressive form of cancer with a poor prognosis, where the operability and hence chance of survival is strongly affected by the tumor infiltration of the arteries. In an effort to enable an automated analysis of the relationship between the local arteries and the tumor, we propose a method for segmenting the peripancreatic arteries in multispectral CT images in the arterial phase. A clinical dataset was collected, and we designed a fast semi-manual annotation procedure, which requires around 20 min of annotation time per case. Next, we trained a U-Net based model to perform binary segmentation of the peripancreatic arteries, where we obtained a near perfect segmentation with a Dice score of 95.05 % in our best performing model. Furthermore, we designed a clinical evaluation procedure for our models; performed by two radiologists, yielding a complete segmentation of 85.31 % of the clinically relevant arteries, thereby confirming the clinical relevance of our method.
Involved external institutions
Germany (DE)How to cite
APA:
Dima, A., Paetzold, J.C., Jungmann, F., Lemke, T., Raffler, P., Kaissis, G.,... Braren, R. (2021). Segmentation of Peripancreatic Arteries in Multispectral Computed Tomography Imaging. In Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 596-605). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
MLA:
Dima, Alina, et al. "Segmentation of Peripancreatic Arteries in Multispectral Computed Tomography Imaging." Proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, Virtual, Online Ed. Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan, Springer Science and Business Media Deutschland GmbH, 2021. 596-605.
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