Ekman M, Lomsky M, Strömblad S O, Carlsson S
Department of Radiation Physics, Sahlgrenska University Hospital, Göteborg, Sweden.
J Nucl Med. 1995 Jun;36(6):1014-8.
Automatic evaluation of left ventricular (LV) function using equilibrium radionuclide angiocardiography requires an edge detection algorithm to correct and reproducibly delineate the left ventricle. Available algorithms, usually based on differentiation of a radial profile, generally suffer from low precision due to low signal-to-noise ratios and overlapping structures, for example, the left atrium.
An edge detection algorithm was developed based on the assumption that the LV border can be defined as the maximum, normalized, closed-line integral of a closed curve in a vector field derived by image differentiation. It is further assumed that the closed curve can be described by a Fourier expansion with a limited number of harmonics. Regions of interest (ROIs) generated by this algorithm were compared with ROIs generated by an algorithm based on a combination of thresholding and second-order derivatives.
This algorithm delineates the left ventricle and gives results more closely related to ROIs generated manually than the algorithm combining thresholding and the second-order derivative. Our algorithm can also handle the problem of overlapping structures, as demonstrated in phantom simulations.
The concept of a maximum, normalized closed-line integral will improve the delineation of the LV in an equilibrium radionuclide angiocardiography study. The problem of overlapping structures is overcome by this algorithm because it takes into consideration global edge information.
使用平衡放射性核素血管造影术自动评估左心室（LV）功能需要一种边缘检测算法来校正并可重复地描绘左心室。现有的算法通常基于径向轮廓的微分，由于信噪比低和结构重叠（例如左心房），一般精度较低。
基于以下假设开发了一种边缘检测算法：左心室边界可定义为通过图像微分得到的向量场中封闭曲线的最大、归一化闭线积分。进一步假设封闭曲线可用有限数量谐波的傅里叶展开来描述。将该算法生成的感兴趣区域（ROI）与基于阈值化和二阶导数组合的算法生成的ROI进行比较。
与结合阈值化和二阶导数的算法相比，该算法描绘左心室的结果与手动生成的ROI更密切相关。如在体模模拟中所示，我们的算法还能处理结构重叠问题。
最大归一化闭线积分的概念将改善平衡放射性核素血管造影术研究中左心室的描绘。该算法克服了结构重叠问题，因为它考虑了全局边缘信息。
