Standard
Generalized Partial Volume : an inferior density estimator to Parzen Windows for normalized mutual information. / Darkner, Sune; Sporring, Jon.
Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings. ed. / Gáboe Székely; Horst K. Hahn. Springer, 2011. p. 436-447 (Lecture notes in computer science, Vol. 6801).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Darkner, S & Sporring, J 2011,
Generalized Partial Volume: an inferior density estimator to Parzen Windows for normalized mutual information. in G Székely & HK Hahn (eds),
Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings. Springer, Lecture notes in computer science, vol. 6801, pp. 436-447, 22nd International Conference on Information Processing in Medical Imaging, Kloster Irsee, Germany,
03/07/2011.
https://doi.org/10.1007/978-3-642-22092-0_36
APA
Darkner, S., & Sporring, J. (2011).
Generalized Partial Volume: an inferior density estimator to Parzen Windows for normalized mutual information. In G. Székely, & H. K. Hahn (Eds.),
Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings (pp. 436-447). Springer. Lecture notes in computer science Vol. 6801
https://doi.org/10.1007/978-3-642-22092-0_36
Vancouver
Darkner S, Sporring J.
Generalized Partial Volume: an inferior density estimator to Parzen Windows for normalized mutual information. In Székely G, Hahn HK, editors, Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings. Springer. 2011. p. 436-447. (Lecture notes in computer science, Vol. 6801).
https://doi.org/10.1007/978-3-642-22092-0_36
Author
Darkner, Sune ; Sporring, Jon. / Generalized Partial Volume : an inferior density estimator to Parzen Windows for normalized mutual information. Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings. editor / Gáboe Székely ; Horst K. Hahn. Springer, 2011. pp. 436-447 (Lecture notes in computer science, Vol. 6801).
Bibtex
@inproceedings{169918b18d854f2c84de3f51af9e9f01,
title = "Generalized Partial Volume: an inferior density estimator to Parzen Windows for normalized mutual information",
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.",
author = "Sune Darkner and Jon Sporring",
year = "2011",
doi = "10.1007/978-3-642-22092-0_36",
language = "English",
isbn = "978-3-642-22091-3",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "436--447",
editor = "G{\'a}boe Sz{\'e}kely and Hahn, {Horst K.}",
booktitle = "Information Processing in Medical Imaging",
address = "Switzerland",
note = "null ; Conference date: 03-07-2011 Through 08-07-2011",
}
RIS
TY - GEN
T1 - Generalized Partial Volume
AU - Darkner, Sune
AU - Sporring, Jon
N1 - Conference code: 22
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-642-22092-0_36
DO - 10.1007/978-3-642-22092-0_36
M3 - Article in proceedings
SN - 978-3-642-22091-3
T3 - Lecture notes in computer science
SP - 436
EP - 447
BT - Information Processing in Medical Imaging
A2 - Székely, Gáboe
A2 - Hahn, Horst K.
PB - Springer
Y2 - 3 July 2011 through 8 July 2011
ER -