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Proceedings Paper

Deformable registration using scale space keypoints
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Paper Abstract

In this paper, we describe a new methodology for keypoint-based affine and deformable medical image registration. This fast and computationally efficient method is automatic and does not rely on segmentation of images. The keypoint pixels used in this technique are extreme points in the scale space and are characterized by descriptor vectors which summarize the intensity gradient profile of the surrounding pixels. For each of the keypoints in the scene image, a corresponding keypoint is identified in the model image using the feature space nearest neighbor criteria. For deformable registration, B-splines are used to extrapolate a regular deformation grid for all of the pixels in the scene image based on the relative displacement vectors of the corresponding pairs. This approach results in a fast and accurate registration in the brain MRI images (an average target registration error of less than 2mm was acquired). We have also studied the affine registration problem in the liver ultrasound and brain MRI images and have acquired acceptable registrations using a mean square solution for affine parameters based on only around 30 corresponding keypoint pairs.

Paper Details

Date Published: 10 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61442G (10 March 2006); doi: 10.1117/12.652132
Show Author Affiliations
Mehdi Moradi, Queen's Univ. (Canada)
Purang Abolmaesoumi, Queen's Univ. (Canada)
Parvin Mousavi, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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