Metal Artifact Reduction via Segmentation and Interpolation
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Resource Overview
MATLAB implementation for metal artifact removal using mean shift segmentation and spline interpolation techniques. This algorithm processes medical images by first partitioning metal-affected regions then reconstructing missing data through smooth interpolation.
Detailed Documentation
This MATLAB program implements a metal artifact removal approach combining segmentation and interpolation methodologies. The algorithm begins by applying mean shift segmentation to partition the image into homogeneous regions, effectively isolating metal-affected areas through clustering based on color/intensity features. Subsequently, spline interpolation reconstructs the corrupted image regions by generating smooth curves that pass through known data points, preserving anatomical structures while eliminating streak artifacts. Key functions include customized bandwidth selection for mean shift clustering and cubic spline interpolation with boundary condition handling. This implementation significantly improves image quality by reducing metal-induced artifacts while maintaining structural integrity, particularly valuable for CT and MRI medical imaging applications.
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