Reconstruction of real object often involves branching contour cases. An effective technique is required to determine the correct corresponding sub contour between two connected contours. This is to ensure the accuracy of the resulted image. This study has introduced a contour matching method using the similarity of the sub contour centroid value. The technique is fast enough equivalence to the  requirement of reconstruction technique which has to be time and space effective. The matched sub contours then are connected by introducing an intermediate contour called as composite contour. The technique has been applied in the reconstruction of human head and Stanford bunny from CT images. Beta-spline was employed as the fitted surface as this surface has capability to give smoothed and accurate result.

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This paper focuses on multi-slice image reconstruction for CT images using Beta-spline. In reconstructing multi-slice images especially from living image, issues like continuity and accuracy contours arise. Commonly, high continuity is hard to be achieved because of the accuracy requirement and vice versa. Thus the image reconstruction process is prolonged to fulfill these constraints. This paper used cubic Beta-spline as the fitted surface in the image reconstruction process. Beta-spline is already has G 2 continuity which is unaffected by the changes in data points position. Surface fitting using Beta-spline has also simplified the branching surface case with the preserved continuity. This study shows the whole image reconstruction process using cubic Beta-spline, and the data used are CT images of human head, Stanford bunny and human pelvic.The produced images show that Beta-spline has capability to produce necessary images within the required continuity and accuracy.

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