Abstract
We derive herein first and second-order differential operators for detecting structure in diffusion tensor MRI (DTI). Unlike existing methods, we are able to generate full first and second-order differentials without dimensionality reduction and while respecting the underlying manifold of the data. Further, we extend corner and curvature feature detectors to DTI using our differential operators. Results using the feature detectors on diffusion tensor MR images show the ability to highlight structure within the image that existing methods cannot.
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Krishna Nand, K., Abugharbieh, R., Booth, B.G., Hamarneh, G. (2011). Detecting Structure in Diffusion Tensor MR Images. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23629-7_12
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DOI: https://doi.org/10.1007/978-3-642-23629-7_12
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