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Disambiguation of "Vandermeulen, Dirk"

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Automatic Segmentation of Brain Tissues and MR Bias Field Correction Using a Cigital Brain Atlas.

, , , and . MICCAI, volume 1496 of Lecture Notes in Computer Science, page 1222-1229. Springer, (1998)

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Guido Vandermeulen

Daniel Dirkmann

In-vitro-Untersuchungen zum Effekt von Hypothermie und Azidose auf Variablen thrombelastometrischer Messungen der Blutgerinnung. Uni Duisburg-Essen, (2009)

Dieter Dirksen

Dorothea Dirksen

Richard Dirkmann

 

Other publications of authors with the same name

Robust initialization for 2D/3D registration of knee implant models to single-plane fluoroscopy., , , , and . Medical Imaging: Image Processing, volume 6512 of SPIE Proceedings, page 651208. SPIE, (2007)Isometric deformation invariant 3D shape recognition., , , and . Pattern Recognit., 45 (7): 2817-2831 (2012)meshSIFT: Local surface features for 3D face recognition under expression variations and partial data., , , and . Comput. Vis. Image Underst., 117 (2): 158-169 (2013)An information theoretic approach for non-rigid image registration using voxel class probabilities., , , and . Medical Image Anal., 10 (3): 413-431 (2006)A Unifying Framework for Partial Volume Segmentation of Brain MR Images., , , and . IEEE Trans. Med. Imaging, 22 (1): 105-119 (2003)Automated Segmentation of MS Lesions from Multi-channel MR Images., , , , , and . MICCAI, volume 1679 of Lecture Notes in Computer Science, page 11-21. Springer, (1999)Active Shape Model-Based Segmentation of Digital X-ray Images., , , , and . MICCAI, volume 1679 of Lecture Notes in Computer Science, page 128-137. Springer, (1999)Validation of Nonlinear Spatial Filtering to Improve Tissue Segmentation of MR Brain Images., , , , and . MICCAI, volume 2208 of Lecture Notes in Computer Science, page 507-515. Springer, (2001)Integrating Statistical Shape Models into a Graph Cut Framework for Tooth Segmentation., , and . MLMI, volume 7588 of Lecture Notes in Computer Science, page 242-249. Springer, (2012)Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging., , , , , , , , , and 30 other author(s). CoRR, (2020)