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Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in CT data for lung cancer staging., , , , and . Int. J. Comput. Assist. Radiol. Surg., 14 (6): 977-986 (2019)Fast meningioma segmentation in T1-weighted MRI volumes using a lightweight 3D deep learning architecture., , , , , and . CoRR, (2020)Train smarter, not harder: learning deep abdominal CT registration on scarce data., , , , , , , and . CoRR, (2022)Vision-based and marker-less surgical tool detection and tracking: a review of the literature., , , and . Medical Image Anal., (2017)Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms., , , , and . CoRR, (2021)Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding., , , , and . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 11 (1): 44-58 (January 2023)Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding., , , , and . CoRR, (2021)Automatic data-driven real-time segmentation and recognition of surgical workflow., , , , and . Int. J. Comput. Assist. Radiol. Surg., 11 (6): 1081-1089 (2016)Automatic knowledge-based recognition of low-level tasks in ophthalmological procedures., , , and . Int. J. Comput. Assist. Radiol. Surg., 8 (1): 39-49 (2013)Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images., , , , , , , , and . CoRR, (2021)