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Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes

M. Kloenne, S. Niehaus, L. Lampe, A. Merola, J. Reinelt, I. Roeder, and N. Scherf. Sci. Rep., 10 (1): 10712 (July 2020)

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A pattern-based approach to a cell tracking ontologyP. Burek, N. Scherf, and H. Herre. Procedia Comput. Sci., (2019)Multi-scale imaging and analysis identify pan-embryo cell dynamics of germlayer formation in zebrafishG. Shah, K. Thierbach, B. Schmid, J. Waschke, A. Reade, M. Hlawitschka, I. Roeder, N. Scherf, and J. Huisken. Nat. Commun., 10 (1): 5753 (December 2019)Benchmarking Large Language Models for Bio-Image Analysis Code GenerationR. Haase, C. Tischer, J. H�rich�, and N. Scherf. (April 2024)Open Problem: Active Representation LearningN. Milosevic, G. M�ller, J. Huisken, and N. Scherf. (2024)Forensic age estimation with Bayesian convolutional neural networks based on panoramic dental X-ray imagingW. de Back, S. Seurig, S. Wagner, B. Marré, I. Roeder, and N. Scherf. (2019)On the ontological foundations of cellular developmentP. Burek, N. Scherf, and H. Herre. (May 2020)A standardized clinical data harmonization pipeline for scalable ai application deployment (fhir-dhp): Validation and usability studyE. Williams, M. Kienast, E. Medawar, J. Reinelt, A. Merola, S. Klopfenstein, A. Flint, P. Heeren, A. Poncette, F. Balzer and 2 other author(s). JMIR Medical Informatics, (2023)Ontology patterns for the representation of quality changes of cells in timeP. Burek, N. Scherf, and H. Herre. J. Biomed. Semantics, 10 (1): 16 (October 2019)Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learningL. Maiello, L. Ball, M. Micali, F. Iannuzzi, N. Scherf, R. Hoffmann, M. Gama de Abreu, P. Pelosi, and R. Huhle. Front. Physiol., (2021)Domain-specific cues improve robustness of deep learning-based segmentation of CT volumesM. Kloenne, S. Niehaus, L. Lampe, A. Merola, J. Reinelt, I. Roeder, and N. Scherf. Sci. Rep., 10 (1): 10712 (July 2020)

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Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes

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Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes