针对基于CT(computed tomography)图像检测分析中的点云提取精度与完整性问题,提出一种基于预分割轮廓的高精度、高完整性的亚体素表面检测方法。首先采用Otsu分割算法提取CT图像的体素级轮廓点集,并以此作为粗定位轮廓自适应地生成用于亚体素表面检测的完备感兴趣区域(region of interest,ROI);然后提出一种基于梯度非极大值抑制的表面体素判定方法,避免了梯度阈值选择难题;最后基于3D Facet模型定位亚体素级表面点位置。实验结果表明,该方法能有效改善传统亚体素检测方法的轮廓丢失、伪边严重等问题,轮廓定位误差小于0.2个体素,同时能够取得3倍以上的计算加速比。
Cone-beam computed tornography （CBCT） has the notable features of high efficiency and high precision, and is widely used in areas such as medical imaging and industrial non-destructive testing. However, the presence of the ray scatter reduces the quality of CT images. By referencing the slit collimation approach, a scatter correction method for CBCT based on the interlacing-slit scan is proposed. Firstly, according to the characteristics of CBCT imaging, a scatter suppression plate with interlacing slits is designed and fabricated. Then the imaging of the scatter suppression plate is analyzed, and a scatter correction Calculation method for CBCT based on the image fusion is proposed, which can splice out a complete set of scatter suppression projection images according to the interlacing-slit projection images of the left and the right imaging regions in the scatter suppression plate, and simultaneously complete the scatter correction within the fiat panel detector （FPD）. Finally, the overall process of scatter suppression and correction is provided. The experimental results show that this method can significantly improve the clarity of the slice images and achieve a good scatter correction.
