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Registration of vascular structures using a hybrid mixture model.

, , , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 14 (9): 1507-1516 (2019)

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Interactive Neural Network Robot User Investigation for Medical Image Segmentation., , , and . Bildverarbeitung für die Medizin, page 56-61. Springer Vieweg, (2019)Localisation and characterisation of brain pathology from structural MRI data. University of Freiburg, Germany, (2016)base-search.net (ftunivfreiburg:oai:freidok.uni-freiburg.de:11043).Registration of vascular structures using a hybrid mixture model., , , , , , , , , and 1 other author(s). Int. J. Comput. Assist. Radiol. Surg., 14 (9): 1507-1516 (2019)Intraoperative Brain Shift Compensation Using a Hybrid Mixture Model., , , , , , , and . MICCAI (4), volume 11073 of Lecture Notes in Computer Science, page 116-124. Springer, (2018)Bimodal Nonrigid Registration of Brain MRI Data With Deconvolution of Joint Statistics., , and . IEEE Trans. Image Processing, 23 (9): 3999-4009 (2014)Non-Parametric Bayesian Registration (NParBR) of Body Tumors in DCE-MRI Data., , , and . IEEE Trans. Med. Imaging, 35 (4): 1025-1035 (2016)A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems., , , , , , and . Int. J. Biomedical Imaging, (2019)Bi-modal Non-rigid Registration of Brain MRI Data Based on Deconvolution of Joint Statistics., , and . MBIA, volume 8159 of Lecture Notes in Computer Science, page 40-50. Springer, (2013)