Abstract
Brain atlases are commonly used in a number of applications such as MRI segmentation and surgery targetting. Our goal is to register a basal ganglia atlas to a subject using MR image registration. Existing registration methods are for the most part either too constrained (linear registration) or can deform deep brain ROIs into implausible anatomical shapes.
We developed a block-matching registration method suitable for atlas registration, using a new confidence-based regularization of the vector field. The method was used to register a set of 17 manually segmented MRI onto one subject. Results show that basal ganglia structures were better registered than when using an affine registration method.
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Keywords
- Manual Segmentation
- Registration Method
- Regularization Process
- Nonlinear Registration
- Basal Ganglion Structure
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Bhattacharjee, M., Pitiot, A., Roche, A., Dormont, D., Bardinet, E. (2008). Anatomy-Preserving Nonlinear Registration of Deep Brain ROIs Using Confidence-Based Block-Matching. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008. MICCAI 2008. Lecture Notes in Computer Science, vol 5242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85990-1_115
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DOI: https://doi.org/10.1007/978-3-540-85990-1_115
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