ID 原文 译文
23145 因此，结合显著性区域，该文提出一种基于边缘信息与区域局部信息结合的变水平集图像快速分割方法。 Thus, combined with the saliency detection algorithm, a new image segmentation method of variable level set based on the combination of edge information and regional local information is proposed.
23146 首先用元胞自动机模型检测出图像的显著性区域，得到图像的初始化边界曲线。 Firstly, the saliency region of the image is detected by the cellular automata model to obtain initial boundary curve of the image.
23147 然后，采用改进的距离正规化水平集演化(Distance Regularized Level Set Evolution, DRLSE)模型把图像的局部信息结合到变分能量方程中，用改进的能量方程去指导曲线的演化。 Then, an improved distance normalized level  set  evolution  (Distance  Regularized  Level  Set  Evolution,  DRLSE)  model  is  used  to  combine  the  local information of the image into the variational energy equation, and the evolution of the curve is guided by the improved energy equation.
23148 实验结果表明，与 DRLSE 模型相比，提出的算法平均消耗的时间只需要前者的 2.76%，且具有较高的分割准确性。 Compared with the DRLSE, the experimental results show that the average time of the proposed algorithm only needs 2.76% of the former with further improvements in the accuracy of image segmentation.
23149 心脏疾病是全球发病率和死亡率最高的疾病，心音听诊可以获取心脏的机械特性及结构特征，与超声心动图、核磁共振等无创诊断技术相比具有快速、低成本和操作简单的优势。 Heart disease is of highest morbidity and mortality. The cardiac structure and mechanical characteristics can be reflected by auscultation. Compared with echocardiography and nuclear magnetic resonance, auscultation gets the advantages of fast, low cost and easy to use.
23150 心音信号成分复杂，容易受到各种噪声和干扰的影响，听诊诊断结果容易受到医生主观性的影响，极大限制了心音听诊的应用。 The composition of phonocardiogram is complex, and the auscultation is easy to be affected by the subjectivity of the doctor, various noise and disturbances, which limits the application of auscultation.
23151 该文提出一种基于心动周期估计的心音分割及异常心音筛查算法，预先估计了心音的心动周期，存在随机干扰的情况下也可以正确识别信号中80%以上的心动周期，提高了算法的稳定性。 The algorithm of phonocardiogram segmentation and abnormal phonocardiogram screening is presented. For the reason that the heart cycle is estimated in advance, 80% cardiac cycle can be recognition correctly when random disturbances exist.
23152 同时提出了区分度良好的时域和频域特征指标，利用支持向量机建模，对异常心音的识别率可达 92%。 The diagnostic indexes of time and frequency domain with high discrimination are also presented, and the abnormal heart sounds are recognized by Support Vector Machine (SVM) with the accuracy about 92%.
23153 算法可辅助医生诊断，或用于家用便携式心音监护设备。 The algorithm can be used for assisting doctors or portable phonocardiogram monitoring device.
23154 参考信号信杂比(SCR)是评估外辐射源雷达积累增益损失的重要参数。 Signal-Clutter-Ratio (SCR) in reference channel is an important parameter for the evaluation of integration loss of passive radar.