Deformable registration of multi-modal data including rigid structures

Journal Article · Fri May 02 04:00:00 EDT 2003 · IEEE Transactions on Nuclear Science

DOI:https://doi.org/10.1109/TNS.2003.812443· OSTI ID:816367

Huesman, Ronald H ^[1]; Klein, Gregory J; Kimdon, Joey A; Kuo, Chaincy; Majumdar, Sharmila

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1. LBNL Library

Multi-modality imaging studies are becoming more widely utilized in the analysis of medical data. Anatomical data from CT and MRI are useful for analyzing or further processing functional data from techniques such as PET and SPECT. When data are not acquired simultaneously, even when these data are acquired on a dual-imaging device using the same bed, motion can occur that requires registration between the reconstructed image volumes. As the human torso can allow non-rigid motion, this type of motion should be estimated and corrected. We report a deformation registration technique that utilizes rigid registration for bony structures, while allowing elastic transformation of soft tissue to more accurately register the entire image volume. The technique is applied to the registration of CT and MR images of the lumbar spine. First a global rigid registration is performed to approximately align features. Bony structures are then segmented from the CT data using semi-automated process, and bounding boxes for each vertebra are established. Each CT subvolume is then individually registered to the MRI data using a piece-wise rigid registration algorithm and a mutual information image similarity measure. The resulting set of rigid transformations allows for accurate registration of the parts of the CT and MRI data representing the vertebrae, but not the adjacent soft tissue. To align the soft tissue, a smoothly-varying deformation is computed using a thin platespline(TPS) algorithm. The TPS technique requires a sparse set of landmarks that are to be brought into correspondence. These landmarks are automatically obtained from the segmented data using simple edge-detection techniques and random sampling from the edge candidates. A smoothness parameter is also included in the TPS formulation for characterization of the stiffness of the soft tissue. Estimation of an appropriate stiffness factor is obtained iteratively by using the mutual information cost function on the result of the global deformable transformation.

• Research Organization: Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
• Sponsoring Organization: National Institutes of Health (US)
• DOE Contract Number: AC03-76SF00098
• OSTI ID: 816367
• Report Number(s): LBNL--52597
• Journal Information: IEEE Transactions on Nuclear Science, Journal Name: IEEE Transactions on Nuclear Science Journal Issue: 3 Vol. 50; ISSN 0018-9499; ISSN IETNAE
• Country of Publication: United States
• Language: English

Related Subjects

62 RADIOLOGY AND NUCLEAR MEDICINE
ALGORITHMS
DEFORMATION
FLEXIBILITY
FUNCTIONALS
PROCESSING
ROUGHNESS
SAMPLING
SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY
TRANSFORMATIONS
VERTEBRAE
X-RAY CT MRI REGISTRATION MUTLIMODALITY LUMBAR SPINE RIGID ELASTIC