Matching analogous contours is of central importance in computer vision. In this paper, a new hierarchical finite difference method to match analogous contours is presented. In deriving this method, we have been inspired by a method due to Duncan2, who proposed a scheme for matching two contours based on the minimisation of a quadratic fitting criterion. This criterion consists of a curvature dependent bending energy term and a smoothness term. The innovation of our work is in the incorporation of a new smoothness term in the fitting criterion. As a direct consequence, the computational complexity is reduced and the equation corresponding to the minimisation of the fitting criterion is attributed a simple interpretation. The solution method itself is based on a standard finite difference approach. To improve the convergence of the matching process, a new multi-smoothing scheme is proposed. Experimental validation is carried out on three medical applications: (i) Matching of left ventricular contours in successive images of a time sequence of spin echo cardiac magnetic resonance (MR) images, (ii) Matching of brain object contours in consecutive slices of a digital brain atlas, (iii) Matching of brain object contours in segmented MR images to the outlines of the corresponding brain objects in a digital anatomical atlas.
Truyen, B, Pratikakis, I, Xin, Y & Cornelis, J 1995, Hierarchical matching of deformable curves in medical images. in Proceedings IWSSIP 1995, 2nd International Workshop on Image and Signal Processing, Theory, Methodology, Systems and Applications. pp. 284-291, IWSSIP 1995, 2nd International Workshop on Image and Signal Processing: Theory, Methodology, Systems and Applications, Budapest, Hungary, 8/10/95.
Truyen, B., Pratikakis, I., Xin, Y., & Cornelis, J. (1995). Hierarchical matching of deformable curves in medical images. In Proceedings IWSSIP 1995, 2nd International Workshop on Image and Signal Processing, Theory, Methodology, Systems and Applications (pp. 284-291)
@inproceedings{53aea5d029bf44febdd512df02d5ec31,
title = "Hierarchical matching of deformable curves in medical images",
abstract = "Matching analogous contours is of central importance in computer vision. In this paper, a new hierarchical finite difference method to match analogous contours is presented. In deriving this method, we have been inspired by a method due to Duncan2, who proposed a scheme for matching two contours based on the minimisation of a quadratic fitting criterion. This criterion consists of a curvature dependent bending energy term and a smoothness term. The innovation of our work is in the incorporation of a new smoothness term in the fitting criterion. As a direct consequence, the computational complexity is reduced and the equation corresponding to the minimisation of the fitting criterion is attributed a simple interpretation. The solution method itself is based on a standard finite difference approach. To improve the convergence of the matching process, a new multi-smoothing scheme is proposed. Experimental validation is carried out on three medical applications: (i) Matching of left ventricular contours in successive images of a time sequence of spin echo cardiac magnetic resonance (MR) images, (ii) Matching of brain object contours in consecutive slices of a digital brain atlas, (iii) Matching of brain object contours in segmented MR images to the outlines of the corresponding brain objects in a digital anatomical atlas.",
keywords = "contour matching, quadratic fitting criterion, finite difference approach, left ventricular contours, brain object contours",
author = "Bart Truyen and Ioanis Pratikakis and Yang Xin and Jan Cornelis",
year = "1995",
language = "English",
pages = "284--291",
booktitle = "Proceedings IWSSIP 1995, 2nd International Workshop on Image and Signal Processing, Theory, Methodology, Systems and Applications",
note = "IWSSIP 1995, 2nd International Workshop on Image and Signal Processing: Theory, Methodology, Systems and Applications ; Conference date: 08-10-1995 Through 12-10-1995",
}