DocumentCode :
724947
Title :
Quasi real-time sub-space 3D deformable fusion
Author :
Singh, Bharat ; Alchatzidis, Stavros ; Paragios, Nikos
Author_Institution :
Ecole Centrale Paris, Chatenay-Malabry, France
fYear :
2015
fDate :
16-19 April 2015
Firstpage :
833
Lastpage :
836
Abstract :
In this paper we propose a novel and robust approach for de-formable fusion using a metric defined in an appropriate subspace which is adaptive to the image-content/image-modality. We adopt a graph-based formulation that assumes that intensities of corresponding pixels in the two image domains are related through an unknown piece-wise constant linear function. This relation is propagated to an appropriate sub-space (wavelets coefficients) where a criterion that couples the estimation of the deformation field with optimal transport function on the subspace and the smoothness of the deformation is considered. Message passing methods efficiently implemented using jump flooding are considered to get the optimal parameters of the deformation field and the transport function. Promising results are obtained in near real-time with a unique parameter setting.
Keywords :
biomechanics; biomedical MRI; brain; computerised tomography; deformation; graph theory; image fusion; image registration; medical image processing; message passing; positron emission tomography; CT images; MR-T1 brain images; PET images; computerised tomography; deformation field estimation; graph-based formulation; image content; image modality; jump flooding; magnetic resonance imaging; message passing methods; optimal transport function; piecewise constant linear function; positron emission tomography; quasi real-time sub-space 3D deformable fusion; wavelets coefficients; Biomedical imaging; Brain; Discrete wavelet transforms; Image registration; Measurement; Optimization; Robustness; deformable image registration; similarity metric; wavelets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location :
New York, NY
Type :
conf
DOI :
10.1109/ISBI.2015.7164000
Filename :
7164000
Link To Document :
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