Paper
29 March 2016 Multi-temporal MRI carpal bone volumes analysis by principal axes registration
Roberta Ferretti, Silvana Dellepiane
Author Affiliations +
Abstract
In this paper, a principal axes registration technique is presented, with the relevant application to segmented volumes. The purpose of the proposed registration is to compare multi-temporal volumes of carpal bones from Magnetic Resonance Imaging (MRI) acquisitions. Starting from the study of the second-order moment matrix, the eigenvectors are calculated to allow the rotation of volumes with respect to reference axes. Then the volumes are spatially translated to become perfectly overlapped.

A quantitative evaluation of the results obtained is carried out by computing classical indices from the confusion matrix, which depict similarity measures between the volumes of the same organ as extracted from MRI acquisitions executed at different moments. Within the medical field, the way a registration can be used to compare multi-temporal images is of great interest, since it provides the physician with a tool which allows a visual monitoring of a disease evolution.

The segmentation method used herein is based on the graph theory and is a robust, unsupervised and parameters independent method. Patients affected by rheumatic diseases have been considered.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roberta Ferretti and Silvana Dellepiane "Multi-temporal MRI carpal bone volumes analysis by principal axes registration", Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97882R (29 March 2016); https://doi.org/10.1117/12.2211054
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Bone

Magnetic resonance imaging

Image segmentation

Image registration

Brain

Image processing

Image analysis

Back to Top