Directional analysis of digitized three-dimensional images by configuration counts

Area of Science:

• Medical image analysis
• Computational geometry
• Stereology

Background:

• Estimating the orientated rose of normal directions is crucial for analyzing 3D structures from digitized data.
• Existing methods often rely on model-based approaches, which may not be optimal for complex biomedical datasets.

Purpose of the Study:

• To present a novel method for estimating the orientated rose of normal directions in three-dimensional (3D) voxel images.
• To introduce a design-based approach for enhanced applicability in biomedical image analysis.

Main Methods:

• The method utilizes counts of informative configurations within n x n x n voxel cubes.
• An algorithm is proposed for identifying all informative configurations.
• A detailed estimation procedure is described, specifically for the n=2 case.

Main Results:

• The study presents a 3D extension of a 2D method for estimating the orientated rose of binary planar images.
• The proposed design-based approach offers advantages over previous model-based techniques.

Conclusions:

• The new method provides a robust way to analyze normal directions in 3D voxelized data.
• The design-based approach enhances the utility of this method for biomedical image analysis applications.