Neubig L, Kist A (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 14223 LNCS
Pages Range: 703-712
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Vancouver, BC, CAN
ISBN: 9783031439001
DOI: 10.1007/978-3-031-43901-8_67
Semantic segmentation is an important task in medical imaging. Typically, encoder-decoder architectures, such as the U-Net, are used in various variants to approach this task. Normalization methods, such as Batch or Instance Normalization are used throughout the architectures to adapt to data-specific noise. However, it is barely investigated which normalization method is most suitable for a given dataset and if a combination of those is beneficial for the overall performance. In this work, we show that by using evolutionary algorithms we can fully automatically select the best set of normalization methods, outperforming any competitive single normalization method baseline. We provide insights into the selection of normalization and how this compares across imaging modalities and datasets. Overall, we propose that normalization should be managed carefully during the development of the most recent semantic segmentation models as it has a significant impact on medical image analysis tasks, contributing to a more efficient analysis of medical data. Our code is openly available at https://github.com/neuluna/evoNMS.
APA:
Neubig, L., & Kist, A. (2023). Evolutionary Normalization Optimization Boosts Semantic Segmentation Network Performance. In Hayit Greenspan, Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 703-712). Vancouver, BC, CAN: Springer Science and Business Media Deutschland GmbH.
MLA:
Neubig, Luisa, and Andreas Kist. "Evolutionary Normalization Optimization Boosts Semantic Segmentation Network Performance." Proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, Vancouver, BC, CAN Ed. Hayit Greenspan, Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor, Springer Science and Business Media Deutschland GmbH, 2023. 703-712.
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