Consistency of parametric registration in serial MRI studies of brain tumor progression
Creators
- 1. University of Luebeck, Institute of Medical Engineering, Luebeck (Germany)
- 2. University of Oxford, Institute of Biomedical Engineering, Department of Engineering Science, Oxford (United Kingdom)
- 3. University College London, Centre for Medical Image Computing, London (United Kingdom)
- 4. King's College London, Centre for Neuro Imaging Sciences, Institute of Psychiatry, London (United Kingdom)
- 5. Universitat Pompeu Fabra, Center for Computational Imaging and Simulation Technologies in Biomedicine, Barcelona (Spain)
- 6. Medicine Research Centre Juelich, Institute of Neuroscience and Biophysics 3, Juelich (Germany)
- 7. University College London, Institute of Neuroradiology, London (United Kingdom)
Description
The consistency of parametric registration in multi-temporal magnetic resonance (MR) imaging studies was evaluated. Serial MRI scans of adult patients with a brain tumor (glioma) were aligned by parametric registration. The performance of low-order spatial alignment (6/9/12 degrees of freedom) of different 3D serial MR-weighted images is evaluated. A registration protocol for the alignment of all images to one reference coordinate system at baseline is presented. Registration results were evaluated for both, multimodal intra-timepoint and mono-modal multi-temporal registration. The latter case might present a challenge to automatic intensity-based registration algorithms due to ill-defined correspondences. The performance of our algorithm was assessed by testing the inverse registration consistency. Four different similarity measures were evaluated to assess consistency. Careful visual inspection suggests that images are well aligned, but their consistency may be imperfect. Sub-voxel inconsistency within the brain was found for allsimilarity measures used for parametric multi-temporal registration. T1-weighted images were most reliable for establishing spatial correspondence between different timepoints. The parametric registration algorithm is feasible for use in this application. The sub-voxel resolution mean displacement error of registration transformations demonstrates that the algorithm converges to an almost identical solution for forward and reverse registration. (orig.)
Availability note (English)
Available from: http://dx.doi.org/10.1007/s11548-008-0234-5Additional details
Identifiers
Publishing Information
- Journal Title
- International Journal of Computer Assisted Radiology and Surgery (Print)
- Journal Volume
- 3
- Journal Issue
- 3-4
- Journal Page Range
- p. 201-211
- ISSN
- 1861-6410
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- Germany
- INIS RN
- 40007973
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ADULTS; ALGORITHMS; BRAIN; CARCINOMAS; DOCUMENTATION; IMAGE PROCESSING; NMR IMAGING; PARAMETRIC ANALYSIS; TIME DEPENDENCE
- Descriptors DEC
- AGE GROUPS; BODY; CENTRAL NERVOUS SYSTEM; DIAGNOSTIC TECHNIQUES; DISEASES; MATHEMATICAL LOGIC; NEOPLASMS; NERVOUS SYSTEM; ORGANS; PROCESSING