Smooth and Regularize Surface

This algorithm is a general purpose surface smoothing algorithm. Multiple resolutions can be used to avoid cusp formation. Six different algorithms are included.

Input Types

You should be able to apply this algorithm to 3D surfaces.

Input Parameters

Method

The method of smoothing. Choose between Taubin, Laplacian, Weighted Laplacian, Bilaplacian, Mean Curvature and Smooth and Regularize

The default value is Weighted Laplacian.

Maximum Iterations

Specifies the maximum number of iterations allowed before the process is terminated.

The default value is 500.

Update Step Size

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The default value is 10.

Multi-resolutions

Specifies the number of resolution levels to use for smoothing the surface.

The default value is 4.

Maximum Decimation (%)

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The default value is 0.5.

Prevent Self-Intersection

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Compute Shape Metrics

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Shape Metrics Resolutions

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The default value is 5.

Smoothing Factor

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The default value is 0.75.

Regularization Factor

<insert description>

The default value is 0.5.

Mean Curvature Threshold

<insert description>

The default value is 40.0.

Lorentzian Norm

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Radial Force

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The default value is 0.0.

Radial Force Fuzziness

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The default value is 0.2.

Example Usage

Example input surface.

 Input Image

Smoothed output surface using Laplacian smoothing.

 Input Image

References


[1] Y. Ohtake, A. Belyaev, and I. Bogaevski, "Mesh regularization and adaptive smoothing", Computer-Aided Design, vol. 33, no. 11, pp. 789-800, 2001.
[2] B. Fischl, M. Sereno, and A. Dale, "Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System", NeuroImage, vol. 9, no. 2, pp. 195-207, 1999.
[3] F. Segonne, E. Grimson, and B. Fischl, "A genetic algorithm for the topology correction of cortical surfaces", Proceedings of Information Processing in Medical Imaging, LNCS, vol. 3565, pp. 393-405, 2005.