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Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks

Robinson R, Dou Q, Coelho de Castro D, Kamnitsas K, de Groot M, Summers RM, Rueckert D, Glocker B (2020)

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Publication Type: Conference contribution

Publication year: 2020

Journal

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 12267 LNCS

Pages Range: 710-719

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Lima, PER

ISBN: 9783030597276

DOI: 10.1007/978-3-030-59728-3_69

Abstract

We investigate the use of image-and-spatial transformer networks (ISTNs) to tackle domain shift in multi-site medical imaging data. Commonly, domain adaptation (DA) is performed with little regard for explainability of the inter-domain transformation and is often conducted at the feature-level in the latent space. We employ ISTNs for DA at the image-level which constrains transformations to explainable appearance and shape changes. As proof-of-concept we demonstrate that ISTNs can be trained adversarially on a classification problem with simulated 2D data. For real-data validation, we construct two 3D brain MRI datasets from the Cam-CAN and UK Biobank studies to investigate domain shift due to acquisition and population differences. We show that age regression and sex classification models trained on ISTN output improve generalization when training on data from one and testing on the other site.

Involved external institutions

How to cite

APA:

Robinson, R., Dou, Q., Coelho de Castro, D., Kamnitsas, K., de Groot, M., Summers, R.M.,... Glocker, B. (2020). Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. In Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 710-719). Lima, PER: Springer Science and Business Media Deutschland GmbH.

MLA:

Robinson, Robert, et al. "Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks." Proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, Lima, PER Ed. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, Springer Science and Business Media Deutschland GmbH, 2020. 710-719.

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