Filtered 2D Contour-Based Reconstruction of 3D STL Model from CT-DICOM Images

📅 2026-01-21
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This study addresses geometric distortions in 3D STL model reconstruction from CT-DICOM images, which often arise from noise and outliers in segmented 2D contours. To mitigate these artifacts, the authors propose a reconstruction pipeline that integrates contour point filtering with Delaunay triangulation. The method begins with image enhancement and threshold-based segmentation to extract initial contours, followed by a dedicated filtering mechanism designed to suppress spurious points induced by low image resolution. High-fidelity 3D models are then generated by layer-wise triangulation and connection of the refined contours. Experimental validation on both synthetic geometric phantoms and region-of-interest (ROI) pelvic anatomies demonstrates that the proposed approach significantly improves geometric accuracy, yielding reconstructions that more faithfully represent true anatomical structures.

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📝 Abstract
Reconstructing a 3D Stereo-lithography (STL) Model from 2D Contours of scanned structure in Digital Imaging and Communication in Medicine (DICOM) images is crucial to understand the geometry and deformity. Computed Tomography (CT) images are processed to enhance the contrast, reduce the noise followed by smoothing. The processed CT images are segmented using thresholding technique. 2D contour data points are extracted from segmented CT images and are used to construct 3D STL Models. The 2D contour data points may contain outliers as a result of segmentation of low resolution images and the geometry of the constructed 3D structure deviate from the actual. To cope with the imperfections in segmentation process, in this work we propose to use filtered 2D contour data points to reconstruct 3D STL Model. The filtered 2D contour points of each image are delaunay triangulated and joined layer-by-layer to reconstruct the 3D STL model. The 3D STL Model reconstruction is verified on i) 2D Data points of basic shapes and ii) Region of Interest (ROI) of human pelvic bone and are presented as case studies. The 3D STL model constructed from 2D contour data points of ROI of segmented pelvic bone with and without filtering are presented. The 3D STL model reconstructed from filtered 2D data points improved the geometry of model compared to the model reconstructed without filtering 2D data points.
Problem

Research questions and friction points this paper is trying to address.

3D STL reconstruction
2D contour outliers
CT-DICOM segmentation
geometry deviation
medical image processing
Innovation

Methods, ideas, or system contributions that make the work stand out.

filtered 2D contours
3D STL reconstruction
DICOM image segmentation
Delaunay triangulation
outlier removal
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