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Related Experiment Videos

Marching cube algorithm: review and trilinear interpolation adaptation for image-based dosimetric models.

D A Rajon1, W E Bolch

  • 1Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611-8300, USA.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|June 25, 2003
PubMed
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This study introduces a novel Marching Cube (MC) algorithm adaptation using trilinear interpolation to reduce voxel effects in 3D medical imaging. This method enhances accuracy for internal radiation dose assessments and reduces data size.

Area of Science:

  • Medical Physics
  • Image Processing
  • Computational Anatomy

Background:

  • Current internal organ dose assessment relies on 3D medical images to model anatomy.
  • Voxel effects from the rectangular shape of image voxels can alter dose calculation outcomes.
  • Existing methods require accurate delineation of tissue interfaces for reliable simulations.

Purpose of the Study:

  • To minimize voxel effects in internal organ dose assessment methodologies.
  • To propose an adaptation of the Marching Cube (MC) algorithm for improved accuracy.
  • To reduce data size and enhance distance measurements in 3D medical images.

Main Methods:

  • A review of Marching Cube (MC) algorithm techniques.
  • Adaptation of the MC algorithm using trilinear interpolation for isosurface generation.

Related Experiment Videos

  • Testing the technique with a mathematical model of trabecular bone.

    • Main Results:

    • The proposed trilinear interpolation method effectively removes voxel effects.
    • The technique generates reliable chord-length distributions across image regions.
    • Reduced data size and accurate distance measurements were achieved.

    Conclusions:

    • The adapted MC algorithm with trilinear interpolation is recommended for internal radiation transport simulations.
    • This technique offers improved accuracy and efficiency for dose assessment using digital medical images.
    • The method shows potential for extension to multiple isosurfaces for complex anatomical structures.