目的:探究2型糖尿病(diabetes mellitus type 2,T2DM)患者单次冠状动脉螺旋CT扫描同时获取的胸椎椎体松质骨CT值与冠状动脉钙化数据的相关性。方法:选取2018年7月至2019年11月期间行256排Revolution螺旋CT扫描的T2DM患者72例作为研究对...目的:探究2型糖尿病(diabetes mellitus type 2,T2DM)患者单次冠状动脉螺旋CT扫描同时获取的胸椎椎体松质骨CT值与冠状动脉钙化数据的相关性。方法:选取2018年7月至2019年11月期间行256排Revolution螺旋CT扫描的T2DM患者72例作为研究对象,并分为冠脉钙化阴性组与阳性组,分析两组患者临床资料、胸椎椎体松质骨CT值的差异,Spearman秩相关分析胸椎椎体松质骨CT值与冠状动脉钙化程度相关指标(累及分支数、严重程度)的相关性。结果:冠状动脉螺旋CT扫描可一次性同步获取T2DM患者冠脉钙化数据及胸椎椎体松质骨CT值并完成一站式靶向分析。T2DM患者冠脉钙化阴性组和阳性组间年龄、性别、高血压史、糖尿病病程及胸椎椎体松质骨CT值差异有统计学意义(P<0.05或P<0.001)。T2DM患者胸椎椎体松质骨CT值与冠状动脉钙化累及分支数(r_(s)=-0.748,P<0.001)、严重程度(r_(s)=-0.846,P<0.001)呈显著负相关。结论:在评估T2DM患者冠状动脉钙化严重程度与骨密度的关系时,可利用螺旋CT冠状动脉扫描同步获取胸椎椎体松质骨CT值反映患者骨密度,从而使患者避免多次接受辐射检查的风险,并节省了时间,降低了成本。展开更多
Medical images 3D reconstruction is an important part in medical image analysis and processing. Although lots of algorithms have been proposed continuously, speed and accuracy cannot conform to actual needs, which has...Medical images 3D reconstruction is an important part in medical image analysis and processing. Although lots of algorithms have been proposed continuously, speed and accuracy cannot conform to actual needs, which has always been the focus topic. In this paper, we propose an Improved Marching Cubes algorithm ( I-MC) based on the surface rendering theory, which implements 3D reconstruction of the vertebrae. Firstly, we preprocessed the original 2D vertebrae CT images with the bilateral-filter denoising algorithm. Secondly, on the basis of the traditional Marching Cubes algorithm, the seed voxels were extracted and the Region Growing algorithm was used to determine all voxels that contain isosurfaces. Then, the Golden Section instead of the traditional linear interpolation was used to calculate the equivalent point, and this method reduced the calculations of public edges. VTK and OpenGL implemented 3D reconstruction of the vertebrae on GPU quickly and accurately. The experimental results show that when compared with the traditional Marching Cubes algorithm and Mesh Simplification Marching Cubes algorithm, the improved algorithm achieves a significant improvement of reconstruction speed while preserving the accurate results. The efficiency of algorithm is improved dramatically. This method is real-time and achieves the goal of efficient 3D reconstruction of vertebrae CT images.展开更多
由于椎骨间的形态差距较小、椎体的结构较为复杂,椎骨的CT图像分割处理近来成为医学研究的热门话题之一.本文针对脊柱CT图像水平集分割方法对初始轮廓敏感问题,提出了基于加权随机森林和水平集模型的有效椎骨CT分割方法WRF-CV(Wighted R...由于椎骨间的形态差距较小、椎体的结构较为复杂,椎骨的CT图像分割处理近来成为医学研究的热门话题之一.本文针对脊柱CT图像水平集分割方法对初始轮廓敏感问题,提出了基于加权随机森林和水平集模型的有效椎骨CT分割方法WRF-CV(Wighted Random forest-Chan Vese).本文方法提取图像的SIFT特征,利用加权随机森林回归算法获得脊柱中心点位置,并将平稳控制演化速度和噪声敏感度的水平集分割模型初始轮廓置于预测中心点处,通过求解能量函数演化方程最小值来实现椎骨分割.本文对5190张CT图像进行了评估,方法在椎骨分割测试中得到较好的分割效果,可以更加有效准确地分割椎骨CT图像.展开更多
文摘目的:探究2型糖尿病(diabetes mellitus type 2,T2DM)患者单次冠状动脉螺旋CT扫描同时获取的胸椎椎体松质骨CT值与冠状动脉钙化数据的相关性。方法:选取2018年7月至2019年11月期间行256排Revolution螺旋CT扫描的T2DM患者72例作为研究对象,并分为冠脉钙化阴性组与阳性组,分析两组患者临床资料、胸椎椎体松质骨CT值的差异,Spearman秩相关分析胸椎椎体松质骨CT值与冠状动脉钙化程度相关指标(累及分支数、严重程度)的相关性。结果:冠状动脉螺旋CT扫描可一次性同步获取T2DM患者冠脉钙化数据及胸椎椎体松质骨CT值并完成一站式靶向分析。T2DM患者冠脉钙化阴性组和阳性组间年龄、性别、高血压史、糖尿病病程及胸椎椎体松质骨CT值差异有统计学意义(P<0.05或P<0.001)。T2DM患者胸椎椎体松质骨CT值与冠状动脉钙化累及分支数(r_(s)=-0.748,P<0.001)、严重程度(r_(s)=-0.846,P<0.001)呈显著负相关。结论:在评估T2DM患者冠状动脉钙化严重程度与骨密度的关系时,可利用螺旋CT冠状动脉扫描同步获取胸椎椎体松质骨CT值反映患者骨密度,从而使患者避免多次接受辐射检查的风险,并节省了时间,降低了成本。
基金Sponsored by the Science and Technology Research Projects of Education Department of Heilongjiang Province(Grant No.12531119)
文摘Medical images 3D reconstruction is an important part in medical image analysis and processing. Although lots of algorithms have been proposed continuously, speed and accuracy cannot conform to actual needs, which has always been the focus topic. In this paper, we propose an Improved Marching Cubes algorithm ( I-MC) based on the surface rendering theory, which implements 3D reconstruction of the vertebrae. Firstly, we preprocessed the original 2D vertebrae CT images with the bilateral-filter denoising algorithm. Secondly, on the basis of the traditional Marching Cubes algorithm, the seed voxels were extracted and the Region Growing algorithm was used to determine all voxels that contain isosurfaces. Then, the Golden Section instead of the traditional linear interpolation was used to calculate the equivalent point, and this method reduced the calculations of public edges. VTK and OpenGL implemented 3D reconstruction of the vertebrae on GPU quickly and accurately. The experimental results show that when compared with the traditional Marching Cubes algorithm and Mesh Simplification Marching Cubes algorithm, the improved algorithm achieves a significant improvement of reconstruction speed while preserving the accurate results. The efficiency of algorithm is improved dramatically. This method is real-time and achieves the goal of efficient 3D reconstruction of vertebrae CT images.
文摘由于椎骨间的形态差距较小、椎体的结构较为复杂,椎骨的CT图像分割处理近来成为医学研究的热门话题之一.本文针对脊柱CT图像水平集分割方法对初始轮廓敏感问题,提出了基于加权随机森林和水平集模型的有效椎骨CT分割方法WRF-CV(Wighted Random forest-Chan Vese).本文方法提取图像的SIFT特征,利用加权随机森林回归算法获得脊柱中心点位置,并将平稳控制演化速度和噪声敏感度的水平集分割模型初始轮廓置于预测中心点处,通过求解能量函数演化方程最小值来实现椎骨分割.本文对5190张CT图像进行了评估,方法在椎骨分割测试中得到较好的分割效果,可以更加有效准确地分割椎骨CT图像.
