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.

翻译：从医学数字成像与通信（DICOM）图像中扫描结构的二维轮廓重建三维立体光刻（STL）模型，对于理解几何形态与畸形结构至关重要。本研究对计算机断层扫描（CT）图像进行对比度增强、噪声抑制及平滑处理。经处理的CT图像通过阈值分割技术进行分割，从分割后的CT图像中提取二维轮廓数据点，并用于构建三维STL模型。由于低分辨率图像分割可能产生异常点，导致重建的三维结构几何形态与实际存在偏差。为应对分割过程中的缺陷，本文提出使用滤波后的二维轮廓数据点重建三维STL模型。对每张图像的滤波二维轮廓点进行Delaunay三角剖分，并通过逐层拼接实现三维STL模型重建。重建方法在以下两方面得到验证：i）基础形状的二维数据点；ii）人体骨盆骨感兴趣区域（ROI），并作为案例研究进行展示。本文展示了使用滤波与未滤波的骨盆骨ROI分割二维轮廓数据点所构建的三维STL模型。实验表明，相较于未滤波二维数据点重建的模型，基于滤波二维数据点重建的三维STL模型在几何保真度上具有显著提升。