25 April 1997 Contour-model-guided nonlinear deformation model for intersubject image registration
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Abstract
An automated method is proposed for anatomic standardization that can elastically map one subject's MRI image to a standard reference MRI image to enable inter-subject and cross-group studies. In this method, linear transformations based on bicommissural stereotaxy are first applied to grossly align the input image to the reference image. Then, generalized Hough transform is applied to find the candidate corresponding regions in the input image based on the contour information from the pre-segmented reference image. Next, an active contour model initialized with the result from the generalized Hough transform is employed to refine the contour description of the input image. Based on the contour correspondence established in the previous steps, a non-linear transformation is determined using the proposed weighted local reference coordinate systems to warp the input image. In this method, geometric correspondence established based on contour matching is used to control the warping and the actual image values corresponding to registered coordinates need not be similar. We tested this algorithm on various synthetic and real images for inter- subject registration of MR images.
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Wen-Shiang Vincent Shih, Wei-Chung Lin, Chin-Tu Chen, "Contour-model-guided nonlinear deformation model for intersubject image registration", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274147; https://doi.org/10.1117/12.274147
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