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

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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
Publication date2011
ISBN (Print)978-3-642-22091-3
ISBN (Electronic)978-3-642-22092-0
Publication statusPublished - 2011
Event22nd International Conference on Information Processing in Medical Imaging - Kloster Irsee, Germany
Duration: 3 Jul 20118 Jul 2011
Conference number: 22


Conference22nd International Conference on Information Processing in Medical Imaging
ByKloster Irsee
SeriesLecture notes in computer science

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