Fast rigid registration in radiation therapy
Based on a stochastic mutual information type matching and RPROP as stochastic optimizer, an interactive image-based registration of a CT volume onto two 2D images provided by a megavoltage system is presented. The matching process is based on semi-automatic pre-segmentation, an approximate 2D-2D ma...
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| Hauptverfasser: | , , , , , |
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| Dokumenttyp: | Kapitel/Artikel Konferenzschrift |
| Sprache: | Englisch |
| Veröffentlicht: |
01 Jan 2006
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| In: |
Medicine meets virtual reality 14
Year: 2006, Pages: 404-406 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://europepmc.org/article/MED/16404087
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| Verfasserangaben: | Ulrich Müller, Jürgen Hesser, Cornelia Walter, Barbara Dobler, Frank Lohr, Frederik Wenz |
| Zusammenfassung: | Based on a stochastic mutual information type matching and RPROP as stochastic optimizer, an interactive image-based registration of a CT volume onto two 2D images provided by a megavoltage system is presented. The matching process is based on semi-automatic pre-segmentation, an approximate 2D-2D matching with precomputed virtual projections (DRRs) followed by an accurate 3D-2D matching step. Our sample-based approach requires only a fraction of computed DRRs for 3D-2D. A simultaneous computation of the DRR rays and their perturbations in 6 dimensions speeds up the rendering process by a factor of 6.8. The complete registration process takes 5.6 +/- 2.3 seconds on a 3 GHz Pentium IV PC, being the fastest non-parallel approach for this sort of application the authors are aware of. |
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| Beschreibung: | Gesehen am 16.03.2022 |
| Beschreibung: | Online Resource |
| ISBN: | 1429402105 9781429402101 9781607501589 1607501589 9781586035839 1586035835 |