Paper
14 November 2007 PCA and level set based non-rigid image registration for MRI and Paxinos-Watson atlas of rat brain
Chao Cai, Ailing Liu, Mingyue Ding, Chengping Zhou
Author Affiliations +
Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 67891S (2007) https://doi.org/10.1117/12.774741
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Image registration provides the ability to geometrically align one dataset with another. It is a basic task in a great variety of biomedical imaging applications. This paper introduced a novel three-dimensional registration method for Magnetic Resonance Image (MRI) and Paxinos-Watson Atlas of rat brain. For the purpose of adapting to a large range and non-linear deformation between MRI and atlas in higher registration accuracy, based on the segmentation of rat brain, we chose the principle components analysis (PCA) automatically performing the linear registration, and then, a level set based nonlinear registration correcting some small distortions. We implemented this registration method in a rat brain 3D reconstruction and analysis system. Experiments have demonstrated that this method can be successfully applied to registering the low resolution and noise affection MRI with Paxinos-Watson Atlas of rat brain.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chao Cai, Ailing Liu, Mingyue Ding, and Chengping Zhou "PCA and level set based non-rigid image registration for MRI and Paxinos-Watson atlas of rat brain", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67891S (14 November 2007); https://doi.org/10.1117/12.774741
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KEYWORDS
Image registration

Brain

Magnetic resonance imaging

Neuroimaging

Principal component analysis

Image segmentation

3D modeling

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