Interpretable Vertebral Fracture Diagnosis
Engstler P, Keicher M, Schinz D, Mach K, Gersing AS, Foreman SC, Goller SS, Weissinger J, Rischewski J, Dietrich AS, Wiestler B, Kirschke JS, Khakzar A, Navab N (2022)
Publication Type: Conference contribution
Publication year: 2022
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 13611 LNCS
Pages Range: 71-81
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Singapore, SGP
ISBN: 9783031179754
DOI: 10.1007/978-3-031-17976-1_7
Abstract
Do black-box neural network models learn clinically relevant features for fracture diagnosis? The answer not only establishes reliability, quenches scientific curiosity, but also leads to explainable and verbose findings that can assist the radiologists in the final and increase trust. This work identifies the concepts networks use for vertebral fracture diagnosis in CT images. This is achieved by associating concepts to neurons highly correlated with a specific diagnosis in the dataset. The concepts are either associated with neurons by radiologists pre-hoc or are visualized during a specific prediction and left for the user’s interpretation. We evaluate which concepts lead to correct diagnosis and which concepts lead to false positives. The proposed frameworks and analysis pave the way for reliable and explainable vertebral fracture diagnosis. The code is publicly available (https://github.com/CAMP-eXplain-AI/Interpretable-Vertebral-Fracture-Diagnosis ).
Involved external institutions
Germany (DE)How to cite
APA:
Engstler, P., Keicher, M., Schinz, D., Mach, K., Gersing, A.S., Foreman, S.C.,... Navab, N. (2022). Interpretable Vertebral Fracture Diagnosis. In Mauricio Reyes, Pedro Henriques Abreu, Jaime Cardoso (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 71-81). Singapore, SGP: Springer Science and Business Media Deutschland GmbH.
MLA:
Engstler, Paul, et al. "Interpretable Vertebral Fracture Diagnosis." Proceedings of the 5th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, Singapore, SGP Ed. Mauricio Reyes, Pedro Henriques Abreu, Jaime Cardoso, Springer Science and Business Media Deutschland GmbH, 2022. 71-81.
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