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Proceedings Paper

A novel class of machine-learning-driven real-time 2D/3D tracking methods: texture model registration (TMR)
Author(s): Philipp Steininger; Markus Neuner; Karl Fritscher; Felix Sedlmayer; Heinrich Deutschmann
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Paper Abstract

We present a novel view on 2D/3D image registration by introducing a generic algorithmic framework that is based on supervised machine learning (SML). First and foremost, this class of algorithms, referred to as texture model registration (TMR), aims at making 2D/3D registration applicable for time-critical image guided medical procedures. TMR methods are two-stage. In a first offline pre-computational stage, a prediction rule is derived from a pre-interventional 3D image and according geometric constraints. This is achieved by computing digitally reconstructed radiographs, pre-processing them, extracting their texture, and applying SML methods. In a second online stage, the inferred rule is used for predicting the spatial rigid transformation of unseen intrainterventional 2D images. A first simple concrete TMR implementation, referred to as TMR-PCR, is introduced. This approach involves principal component regression (PCR) and simple intermediate pre-processing steps. Using TMR-PCR, first experimental results on five clinical IGRT 3D data sets and synthetic intra-interventional images are presented. The implementation showed an average registration rate of 48 Hz over 40000 registrations, and succeeded in the majority of cases with a mean target registration error smaller than 2 mm. Finally, the potential and characteristics of the proposed methodical framework are discussed.

Paper Details

Date Published: 1 March 2011
PDF: 9 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79640G (1 March 2011); doi: 10.1117/12.878147
Show Author Affiliations
Philipp Steininger, Paracelsus Medical Univ. (Austria)
Markus Neuner, Paracelsus Medical Univ. (Austria)
Karl Fritscher, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Felix Sedlmayer, Paracelsus Medical Univ. (Austria)
Heinrich Deutschmann, Paracelsus Medical Univ. (Austria)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes, Editor(s)

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