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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.
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.
Details
Erscheinungsjahr: | 2010 |
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Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: | Einband - flex.(Paperback) |
ISBN-13: | 9783639119541 |
ISBN-10: | 3639119541 |
Sprache: | Englisch |
Autor: | Russakoff, Daniel |
Hersteller: | VDM Verlag Dr. Müller |
Verantwortliche Person für die EU: | OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, D-66111 Saarbrücken, info@akademikerverlag.de |
Maße: | 8 x 150 x 220 mm |
Von/Mit: | Daniel Russakoff |
Erscheinungsdatum: | 31.03.2010 |
Gewicht: | 0,196 kg |
Details
Erscheinungsjahr: | 2010 |
---|---|
Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: | Einband - flex.(Paperback) |
ISBN-13: | 9783639119541 |
ISBN-10: | 3639119541 |
Sprache: | Englisch |
Autor: | Russakoff, Daniel |
Hersteller: | VDM Verlag Dr. Müller |
Verantwortliche Person für die EU: | OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, D-66111 Saarbrücken, info@akademikerverlag.de |
Maße: | 8 x 150 x 220 mm |
Von/Mit: | Daniel Russakoff |
Erscheinungsdatum: | 31.03.2010 |
Gewicht: | 0,196 kg |
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