摘要
设计并实现了一种单光子发射断层成像(SPECT)心肌重建图像的左心室长轴自动定位算法。首先通过迭代阈值方法实现原始图像的分割去噪;然后基于连续区块理论,通过先验知识与约束条件自动提取三维感兴趣区(ROI),排除其他器官与噪声的干扰;下一步对数据进行重采样操作,改善数据质量,并应用形态学中的骨架化算法得到足够的、能够描述心肌轮廓的采样点;在确定合适的、能够在XY方向完整描述心肌形状的平面(α平面)后,通过二次曲线拟合得到XY方向偏角(α角);随后通过插值方法沿α角与Z轴方向获取新的截面(β平面),并在β平面内二次曲线拟合得到仰角β角,α角与β角便给出了左心室长轴的定位。最后,本算法在原始模体数据、重建数据以及含噪声重建数据各49组测试中,全部定位成功,且平均绝对误差小于5°,并对真实临床SPECT心肌图像数据实现了成功自动定位。
A new method was developed to automatically determine the orientation of left ventricular long axis from reconstructed myocardial SPECT images .The method consists following steps:firstly, image segmentation and noise reduction are performed using an iterative thresholding method .Secondly, the 3D cardiac region of interest ( ROI) is automatically extracted with a new serial box -region method , which is enhanced by knowl-edge and constraint conditions .Thirdly, the input volume is resampled in order to achieve enough sampling points for data-fitting.In the final data-fitting step,α-plane which well presents the shape of left ventricu-lar is generated, and the azimuth angle αis computed by quadratic curve fitting on α-plane.Similarly, aβ-plane is then generated by interpolating the volume data along the azimuth αand the axis Z , and the elevationβis computed by quadratic curve fitting on the β-plane, and the orientation of the long axis is defined by (α,β) .The method was applied to three groups of testing images from original phantom images , noiseless recon-structed images and noisy reconstructed images .In each group , 49 images with different (α,β) values were tested .A success rate of 100%was achieved , and the mean absolute estimation error was less than 5 degrees in all cases .The method was successfully applied to real clinical SPECT cardiac image data .We conclude that the proposed method is feasible for calculating (α,β) for clinical SPECT application .
出处
《核电子学与探测技术》
CAS
CSCD
北大核心
2014年第3期388-395,共8页
Nuclear Electronics & Detection Technology
基金
国家自然科学基金项目(10975786)
教育部留学人员回国启动基金项目