2022 - Research.com Computer Science in Netherlands Leader Award
2007 - IEEE Fellow For leadership and contributions to medical imaging
2002 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to biomedical applications of computer vision and pattern recognition, and for service to IAPR.
His primary areas of study are Artificial intelligence, Computer vision, Segmentation, Image processing and Image registration. His research integrates issues of Tomography and Pattern recognition in his study of Artificial intelligence. His Computer vision research incorporates elements of Algorithm, Magnetic resonance imaging and Convolutional neural network.
His study looks at the intersection of Segmentation and topics like Atlas with Image fusion. His study in Image registration is interdisciplinary in nature, drawing from both Stochastic gradient descent, Data mining, Matching, Mutual information and Medical physics. Max A. Viergever has included themes like Information retrieval, Robustness and Computed tomography in his Medical imaging study.
Max A. Viergever focuses on Artificial intelligence, Computer vision, Segmentation, Radiology and Nuclear medicine. His Artificial intelligence study often links to related topics such as Pattern recognition. The study incorporates disciplines such as Visualization and Algorithm in addition to Computer vision.
His study involves Image segmentation and Scale-space segmentation, a branch of Segmentation. His research in Magnetic resonance imaging, Radiography, Medical imaging and Angiography are components of Radiology. His Imaging phantom study combines topics in areas such as Image quality and Biomedical engineering.
His main research concerns Artificial intelligence, Nuclear medicine, Convolutional neural network, Radiology and Segmentation. His Artificial intelligence research incorporates themes from White matter, Diffusion MRI, Computer vision and Pattern recognition. His Diffusion MRI study incorporates themes from Algorithm and Human Connectome Project.
Max A. Viergever interconnects Radiation treatment planning and Radiography in the investigation of issues within Nuclear medicine. His Convolutional neural network research is multidisciplinary, incorporating perspectives in Autoencoder, Ascending aorta, Minimum bounding box, Angiography and Voxel. His work is dedicated to discovering how Segmentation, Coronal plane are connected with Sagittal plane and other disciplines.
Max A. Viergever mainly investigates Artificial intelligence, Convolutional neural network, Radiology, Deep learning and Segmentation. His research in Artificial intelligence intersects with topics in Neuroimaging, Computer vision and Pattern recognition. His Image registration and Field of view study, which is part of a larger body of work in Computer vision, is frequently linked to Nuclear imaging, Intervention and Process, bridging the gap between disciplines.
His studies in Convolutional neural network integrate themes in fields like Sagittal plane, Minimum bounding box, Coronal plane, Angiography and Voxel. Max A. Viergever combines subjects such as Supervised learning, Neuroradiology and Nuclear medicine with his study of Radiology. His studies deal with areas such as Heart disease and Blood pool as well as Segmentation.
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A survey of medical image registration.
J.B.Antoine Maintz;Max A. Viergever.
Medical Image Analysis (1998)
Muliscale Vessel Enhancement Filtering
Alejandro F. Frangi;Wiro J. Niessen;Koen L. Vincken;Max A. Viergever.
medical image computing and computer assisted intervention (1998)
Mutual-information-based registration of medical images: a survey
J.P.W. Pluim;J.B.A. Maintz;M.A. Viergever.
IEEE Transactions on Medical Imaging (2003)
Ridge-based vessel segmentation in color images of the retina
J. Staal;M.D. Abramoff;M. Niemeijer;M.A. Viergever.
IEEE Transactions on Medical Imaging (2004)
elastix : A Toolbox for Intensity-Based Medical Image Registration
S. Klein;M. Staring;K. Murphy;M.A. Viergever.
IEEE Transactions on Medical Imaging (2010)
Efficient and reliable schemes for nonlinear diffusion filtering
J. Weickert;B.M.T.H. Romeny;M.A. Viergever.
IEEE Transactions on Image Processing (1998)
Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques
West J;Fitzpatrick Jm;Wang My;Dawant Bm.
Journal of Computer Assisted Tomography (1997)
Medical image matching-a review with classification
P.A. van den Elsen;E.-J.D. Pol;M.A. Viergever.
IEEE Engineering in Medicine and Biology Magazine (1993)
Image registration by maximization of combined mutual information and gradient information
J.P.W. Pluim;J.B.A. Maintz;M.A. Viergever.
medical image computing and computer assisted intervention (2000)
Three-dimensional modeling for functional analysis of cardiac images, a review
A.F. Frangi;W.J. Niessen;M.A. Viergever.
IEEE Transactions on Medical Imaging (2001)
Computers in Biology and Medicine
(Impact Factor: 6.698)
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