Generalized Partial Volume: an inferior density estimator to Parzen Windows for normalized mutual information

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Abstract

Mutual Information (MI) and normalized mutual information (NMI) are popular choices as similarity measure for multimodal image registration. Presently, one of two approaches is often used for estimating these measures: The Parzen Window (PW) and the Generalized Partial Volume (GPV). Their theoretical relation has so far been unexplored. We present the direct connection between PW and GPV for NMI in the case of rigid and non-rigid image registration. Through step-by-step derivations of PW and GPV we clarify the difference and show that GPV is algorithmically inferior to PW from a model point of view as well as w.r.t. computational complexity. Finally, we present algorithms for both approaches for NMI which is comparable in speed to Sum of Squared Differences (SSD), and we illustrate the differences between PW and GPV on a number of registration examples.

Original languageEnglish
Title of host publicationInformation Processing in Medical Imaging : 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings
EditorsGáboe Székely, Horst K. Hahn
Number of pages12
PublisherSpringer
Publication date2011
Pages436-447
ISBN (Print)978-3-642-22091-3
ISBN (Electronic)978-3-642-22092-0
DOIs
Publication statusPublished - 2011
Event22nd International Conference on Information Processing in Medical Imaging - Kloster Irsee, Germany
Duration: 3 Jul 20118 Jul 2011
Conference number: 22

Conference

Conference22nd International Conference on Information Processing in Medical Imaging
Number22
Country/TerritoryGermany
CityKloster Irsee
Period03/07/201108/07/2011
SeriesLecture notes in computer science
Volume6801
ISSN0302-9743

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