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Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow

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Gatidis,  Sergios
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;
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Hering, A., Westphal, M., Gerken, A., Almansour, H., Maurer, M., Geisler, B., et al. (2024). Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow. International journal of computer assisted radiology and surgery: a journal for interdisciplinary research, development and applications of image guided diagnosis and therapy, 19, 1689-1697. doi:10.1007/s11548-024-03181-4.


Cite as: https://hdl.handle.net/21.11116/0000-0010-5FC2-9
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