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Synopsis
Intensity-based 2D-3D medical image registration is a special case of the pose estimation problem from computer vision with many applications in medicine. This work presents an overview of the 2D-3D intensity-based image registration problem in the medical domain as well as results from several methods developed to aid in its practice. In particular: 1) Light field rendering techniques from the graphics community are extended to rapidly generate digitally reconstructed radiographs (DRRs). 2) A full 2D-3D registration algorithm using light field DRRs is presented and validated against a real, clinical gold standard. 3) A new, hybrid similarity measure is presented that is a weighted combination of an intensity-based image similarity measure and a point-based measure incorporating a single fiducial marker. 4) Finally, a novel similarity measure called regional mutual information (RMI) is introduced. RMI is an extension of mutual information which incorporates spatial information in a principled way. The additional spatial information helps make its use as a similarity measure much more robust to initial misregistration than standard mutual information.
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Intensity-based 2D-3D medical image registration is a special case of the pose estimation problem from computer vision with many applications in medicine. This work presents an overview of the 2D-3D intensity-based image registration problem in the medical domain as well as results from several methods developed to aid in its practice. In particular: 1) Light field rendering techniques from the graphics community are extended to rapidly generate digitally reconstructed radiographs (DRRs). 2) A full 2D-3D registration algorithm using light field DRRs is presented and validated against a real, clinical gold standard. 3) A new, hybrid similarity measure is presented that is a weighted combination of an intensity-based image similarity measure and a point-based measure incorporating a single fiducial marker. 4) Finally, a novel similarity measure called regional mutual information (RMI) is introduced. RMI is an extension of mutual information which incorporates spatial information in a principled way. The additional spatial information helps make its use as a similarity measure much more robust to initial misregistration than standard mutual information.
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Intensity-based 2D-3D Medical Image Registration
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VDM Verlag Dr. Müller, 2010
ISBN 10 : 3639119541
ISBN 13 : 9783639119541
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Russakoff DanielDaniel Russakoff received an A.B. in geophysics from Harvard University and his Ph.D. in computer science from Stanford. His research is in computer vision and pattern recognition in general, and medical image anal. N° de réf. du vendeur 4959194
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Intensity-based 2D-3D Medical Image Registration: Algorithms and Analysis
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VDM Verlag Dr. Müller, 2010
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ISBN 13 : 9783639119541
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Intensity-based 2D-3D Medical Image Registration: Algorithms and Analysis
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Intensity-based 2D-3D Medical Image Registration: Algorithms and Analysis
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VDM Verlag Dr. Müller, 2010
ISBN 10 : 3639119541
ISBN 13 : 9783639119541
Neuf
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Intensity-based 2D-3D medical image registration is a special case of the pose estimation problem from computer vision with many applications in medicine. This work presents an overview of the 2D-3D intensity-based image registration problem in the medical domain as well as results from several methods developed to aid in its practice. In particular: 1) Light field rendering techniques from the graphics community are extended to rapidly generate digitally reconstructed radiographs (DRRs). 2) A full 2D-3D registration algorithm using light field DRRs is presented and validated against a real, clinical gold standard. 3) A new, hybrid similarity measure is presented that is a weighted combination of an intensity-based image similarity measure and a point-based measure incorporating a single fiducial marker. 4) Finally, a novel similarity measure called regional mutual information (RMI) is introduced. RMI is an extension of mutual information which incorporates spatial information in a principled way. The additional spatial information helps make its use as a similarity measure much more robust to initial misregistration than standard mutual information. N° de réf. du vendeur 9783639119541
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Intensity-based 2D-3D Medical Image Registration: Algorithms and Analysis
Edité par
VDM Verlag Dr. Müller, 2010
ISBN 10 : 3639119541
ISBN 13 : 9783639119541
Neuf
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