Interpolation methods used in MIPAV

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The registration and transformation algorithms implemented in MIPAV resampes images (if needed) using an interpolation scheme, where anisotropic voxels (or pixels for 2D images) are resampled into isotropic 1 mm cubic voxels. New voxel values are computed using a weighted combination of existing voxel values within a defined neighborhood of the new voxel location. The following interpolation methods are available in this implementation of the registration technique, including Bilinear, Trilinear, B-spline 3-rd order, B-spline 4-th order, Cubic Lagrangian, Quintic Lagrangian, Heptic Lagrangian, and Windowed sinc.

See also: Thévenaz, Blu, and Unser, Interpolation Revisited, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 19, NO. 7, JULY 2000

Bilinear Interpolation

Bilinear interpolation considers the closest 2x2 neighborhood of known pixel values surrounding the unknown pixel. It then takes a weighted average of these 4 pixels to arrive at its final interpolated value. This results in smoother looking images.

See also: Optimized automatic registration 3D