Share Email Print
cover

Proceedings Paper

Overlap invariance of cumulative residual entropy measures for multimodal image alignment
Author(s): Nathan D. Cahill; Julia A. Schnabel; J. Alison Noble; David J. Hawkes
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Cumulative residual entropy (CRE)1,2 has recently been advocated as an alternative to differential entropy for describing the complexity of an image. CRE has been used to construct an alternate form of mutual information (MI),3,4 called symmetric cumulative mutual information (SCMI)5 or cross-CRE (CCRE).6 This alternate form of MI has exhibited superior performance to traditional MI in a variety of ways.6 However, like traditional MI, SCMI suffers from sensitivity to the changing size of the overlap between images over the course of registration. Alternative similarity measures based on differential entropy, such as normalized mutual information (NMI),7 entropy correlation coefficient (ECC)8,9 and modified mutual information (M-MI),10 have been shown to exhibit superior performance to MI with respect to the overlap sensitivity problem. In this paper, we show how CRE can be used to compute versions of NMI, ECC, and M-MI that we call the normalized cumulative mutual information (NCMI), cumulative residual entropy correlation coefficient (CRECC), and modified symmetric cumulative mutual information (M-SCMI). We use publicly available CT, PET, and MR brain images* with known ground truth transformations to evaluate the performance of these CRE-based similarity measures for rigid multimodal registration. Results show that the proposed similarity measures provide a statistically significant improvement in target registration error (TRE) over SCMI.

Paper Details

Date Published: 27 March 2009
PDF: 12 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590I (27 March 2009); doi: 10.1117/12.811585
Show Author Affiliations
Nathan D. Cahill, Univ. of Oxford (United Kingdom)
Carestream Health, Inc. (United States)
Julia A. Schnabel, Univ. of Oxford (United Kingdom)
J. Alison Noble, Univ. of Oxford (United Kingdom)
David J. Hawkes, Ctr. for Medical Image Computing, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

© SPIE. Terms of Use
Back to Top