DocumentCode
64136
Title
Multimodal non-rigid registration methods based on local variability measures in computed tomography and magnetic resonance brain images
Author
Reducindo, Isnardo ; Mejia-Rodriguez, Aldo R. ; Arce-Santana, Edgar R. ; Campos-Delgado, D.U. ; Vigueras-Gomez, Flavio ; Scalco, Elisa ; Bianchi, A.M. ; Cattaneo, Giovanni M. ; Rizzo, Gianluca
Author_Institution
Fac. of Sci., Autonomous Univ. of San Luis Potosi, San Luis Potosi, Mexico
Volume
8
Issue
12
fYear
2014
fDate
12 2014
Firstpage
699
Lastpage
707
Abstract
This paper presents a novel non-rigid multimodal registration method that relies on three basic steps: first, an initial approximation of the deformation field is obtained by a parametric registration technique based on particle filtering; second, an intensity mapping based on local variability measures (LVM) is applied over the two images in order to overcome the multimodal restriction between them; and third, an optical flow method is used in an iterative way to find the remaining displacements of the deformation field. Hence the new methodology offers a solution for multimodal NRR by a quadratic optimisation over a convex surface, which allows independent motion of each pixel, in contrast to methods that parameterise the deformation space. To evaluate the proposed method, a set of magnetic resonance/computed tomography clinical studies (pre- and post-radiotherapy treatment) of three patients with cerebral tumour deformations of the brain structures was employed. The resulting registration was evaluated both qualitatively and quantitatively by standard indices of correspondence over anatomical structures of interest in radiotherapy (brain, tumour and cerebral ventricles). These results showed that one of the proposed LVM (entropy) offers a superior performance in estimating the non-rigid deformation field.
Keywords
approximation theory; biomedical MRI; brain; computerised tomography; image registration; medical image processing; particle filtering (numerical methods); LVM; NRR; anatomical structures; brain ventricles; cerebral ventricles; computed tomography; convex surface; deformation field; deformation space; diagnostic procedures; initial approximation; intensity mapping; local variability measurement; magnetic resonance brain images; magnetic resonance-computed tomography; medical imaging; multimodal images; multimodal nonrigid registration methods; parametric registration technique; particle filtering; quadratic optimisation; radiotherapy; therapeutic procedures; tumour ventricles;
fLanguage
English
Journal_Title
Image Processing, IET
Publisher
iet
ISSN
1751-9659
Type
jour
DOI
10.1049/iet-ipr.2013.0705
Filename
6969746
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