Landmark Optimization Using Local Curvature for Point-Based Nonlinear Rodent Brain Image Registration
Joint Authors
Kielian, Tammy
Sajja, Balasrinivasa R.
Gendelman, Howard E.
Boska, Michael D.
Liu, Yutong
Uberti, Mariano G.
Source
International Journal of Biomedical Imaging
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-09-26
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Purpose.
To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration.
Materials and Methods.
Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed) and target (reference image).
Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks.
The method was evaluated in two cases (n=5 each).
In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected.
Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks.
Results.
Statistical analyses demonstrated significant improvement (P<0.05) in registration accuracy by landmark optimization in most data sets and trends towards improvement (P<0.1) in others as compared to manual landmark selection.
American Psychological Association (APA)
Liu, Yutong& Sajja, Balasrinivasa R.& Uberti, Mariano G.& Gendelman, Howard E.& Kielian, Tammy& Boska, Michael D.. 2011. Landmark Optimization Using Local Curvature for Point-Based Nonlinear Rodent Brain Image Registration. International Journal of Biomedical Imaging،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-486938
Modern Language Association (MLA)
Liu, Yutong…[et al.]. Landmark Optimization Using Local Curvature for Point-Based Nonlinear Rodent Brain Image Registration. International Journal of Biomedical Imaging No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-486938
American Medical Association (AMA)
Liu, Yutong& Sajja, Balasrinivasa R.& Uberti, Mariano G.& Gendelman, Howard E.& Kielian, Tammy& Boska, Michael D.. Landmark Optimization Using Local Curvature for Point-Based Nonlinear Rodent Brain Image Registration. International Journal of Biomedical Imaging. 2011. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-486938
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-486938