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Multimodal Non-Rigid Registration
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Introduction
Medical image registration is a process in which two existing image representations of
anatomy (e.g. MRI, CT, x-ray) or its function (e.g. PET, SPECT, fMRI) are put into
correspondence. Registration approaches differ according to expected and modeled
deformations and can be divided into rigid and nonrigid registrations. We are interested
in nonrigid registration, which can detect and correct discrepancies of small spatial extent,
by deforming one of the images (source) to match the other (reference).
Spatial deformation model can be based on different physical properties like elasticity
or viscosity, or their generalizations and simplifications. Deformation is driven by
external forces, which tend to minimize image differences, measured by image similarity measures.
When images are acquired by different imaging procedures, we are talking about multimodal
image registration. The problem of multimodal registration is in complex relation between
intensities of both images, which is furthermore usually not known in advance. Measuring
of image similarity is in that case based on statistics. The problem is even more difficult
if images are supposed to be registered nonrigidly.
To detect and correct small local image differences, external forces must be estimated
from similarities of small image regions, but statistical significance of such small
image regions is low and similarities are not sufficiently reliable and accurate.
We have focused on multimodal elastic matching to solve the problems mentioned earlier.
We have introduced a new approach for measuring multimodal similarities of small image
regions "point similarity measures". We have also built a system for multimodal nonrigid
registration that is based on these measures. It uses a spatial model that is inspired by
linear elasticity. Furthermore it uses multiresolution approach that improves registration
speed and accuracy.
Publications:
- Peter Rogelj, Stanislav Kovačič. "Symmetric Image Registration".
Medical Image Analysis, 2005.
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- Peter Rogelj, Stanislav Kovačič."Spatial deformation models for non-rigid image registration". In: Danijel Skočaj (ed.), Proceedings of the 9th Computer Vision Winter Workshop, CVWW'04 : 4-6 February 2004, Piran, Slovenia, pp.79-88. Slovenian Pattern Recognition Society, February 2004.
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- Peter Rogelj, Stanislav Kovačič, James C. Gee. "Point similarity measures for non-rigid registration of multi-modal data".
Computer Vision and Image Understanding, 92(1): 112-140, October 2003.
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- Peter Rogelj, Stanislav Kovačič."Point similarity measure based on mutual information". In: James C. Gee, J. B. Antoine Maintz, Michael W. Vannier (eds.), Biomedical Image Registration : revised papers, (Lecture notes in computer science, vol.2717), pp.112-121. Springer-Verlag, June 2003.
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- Peter Rogelj, Stanislav Kovačič."Rigid multi-modality registration of medical images using point similarity measures". In: O. Drbohlav (ed.), Proceedings of the 8th Computer Vision Winter Workshop CVWW'03, pp.159-163. February 2003.
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- Peter Rogelj, Stanislav Kovačič."Validation of a Non-Rigid Registration Algorithm for Multi-Modal Data". In: Milan Sonka, J. Michael Fitzpatrick (eds.), Medical Imaging 2002, Image Processing : 24-28 February 2002, San Diego, USA, (Proceedings of SPIE, vol.4684), pp.299-307. SPIE, Bellingham (USA), February 2002.
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- R. Bajcsy, S. Kovačič. "Multiresolution Elastic Matching".
Computer Vision, Graphics and Image Processing, 46: 1-21, April 1989.
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