Unsupervised Non-correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network

Julia Andresen; Timo Kepp; Jan Ehrhardt; Claus von der Burchard; Johann Roider; Heinz Handels

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Unsupervised Non-correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2022) 13386 LNCS 3-7

DOI: 10.1007/978-3-031-11203-4_1

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Abstract

Medical image registration allows comparing images from different patients, modalities or time-points, but often suffers from missing correspondences due to pathologies and inter-patient variations.

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Andresen, J., Kepp, T., Ehrhardt, J., von der Burchard, C., Roider, J., & Handels, H. (2022). Unsupervised Non-correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13386 LNCS, pp. 3–7). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-11203-4_1

Unsupervised Non-correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network

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