Addendum: B-spline interpolation in medical image processing

Abstract

This paper analyzes B-spline interpolation techniques of degree 2, 4, and 5 with respect to all criteria that have been applied to evaluate various interpolation schemes in a recently published survey on image interpolation in medical imaging (Lehmann et al., 1999). It is shown that high-degree B-spline interpolation has superior Fourier properties, smallest interpolation error, and reasonable computing times. Therefore, high-degree B-splines are preferable interpolators for numerous applications in medical image processing, particularly if high precision is required. If no aliasing occurs, this result neither depends on the geometric transform applied for the tests nor the actual content of images.

A new approach for regularized image interpolation

“…ii-Cubic Spline (8) For the case of bicubic interpolation, the sample values are used as the interpolation coefficients. On the other hand, cubic spline interpolation requires the estimation of the interpolation coefficients using a digital filtering step prior to the interpolation process [1][2][3][4][5][6][7][8][9][10][11][12][13].…”

“…From the numerical computations point of view, the ideal interpolation formula is not practical due to the slow rate of decay of the interpolation kernel sinc(x). So, approximations such as the bicubic and cubic spline interpolation techniques are used as alternatives [1][2][3][4][5][6][7][8][9][10][11][12][13].…”

“…The image interpolation problem has been intensively treated in the literature [1][2][3][4][5][6][7][8][9][10][11][12]. Conventional interpolation algorithms such as the bicubic and cubic spline algorithms have been widely used in image interpolation [1][2][3][4][5][6][7][8][9][10][11][12].…”

“…Conventional interpolation algorithms such as the bicubic and cubic spline algorithms have been widely used in image interpolation [1][2][3][4][5][6][7][8][9][10][11][12]. These conventional algorithms are space invariant algorithms based on the appropriate choice of a basis function.…”

A comparative study on interpolation methods for controlled cardiac CT

“…Many of these comparisons were carried out on some common medical imaging tasks in spatial and/or frequency domains (Maeland, 1988;Lehmann et al, 1999Lehmann et al, , 2001Thevenaz et al, 2000;Meijering et al, 2001;Xu and Mueller, 2006). It is necessary to evaluate the chosen interpolation methods for controlled cardiac CT and is the main goal of this article.…”