Zusammenfassung
Applications in digital histopathology often require costly expert labels to train modern machine learning algorithms. We introduce an adaptation of the Image Quilting algorithm for texture synthesis that is utilized to virtually multiply the tissues and labels. Potential applications are augmentation in neural network training and quality control in intra-rater experiments. We evaluate this method in a subjective expert trial and a quantitative augmented learning scenario.
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© 2020 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Bug, D. et al. (2020). Image Quilting for Histological Image Synthesis. In: Tolxdorff, T., Deserno, T., Handels, H., Maier, A., Maier-Hein, K., Palm, C. (eds) Bildverarbeitung für die Medizin 2020. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-29267-6_72
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DOI: https://doi.org/10.1007/978-3-658-29267-6_72
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