The false positive and false negative rates of current image localization methods in gynecological lesion area are high because the effectiveness is affected by random noise. Therefore, by using Bhattacharyya coefficient-based scale-invariant feature transform (B-SIFT), a novel localization method of lesion area in gynecological ultrasound image is proposed in this paper. Firstly, Rayleigh mean filtering is used to suppress the noise in the ultrasound image based on Rayleigh distribution characteristics of the noise. Then, the segmentation method of the lesion region is designed by using the scale-invariant feature transform (SIFT). Furthermore, the feature extraction function B-SIFT is proposed to locate the lesion region based on the Bhattacharyya coefficient. Finally, two lesion characteristics of Bhattacharyya coefficients are defined, and the B-SIFT-based feature region descriptors are obtained by constructing an eigenvector normalized based on the Bhattacharyya coefficients. Experimental results show that the proposed method has a high positioning accuracy, strong recall ratio, low energy consumption, and low time consumption, which is more effective and feasible than the traditional method for localization of lesions.

由于有效性受到随机噪声的影响，目前在妇科病变区域中图像定位方法的假阳性和假阴性率很高。因此，利用基于Bhattacharyya系数的尺度不变特征变换（B-SIFT），提出了一种新的妇科超声图像病变部位定位方法。首先，基于噪声的瑞利分布特征，使用瑞利均值滤波来抑制超声图像中的噪声。然后，使用尺度不变特征变换（SIFT）设计病变区域的分割方法。此外，提出了基于Bhattacharyya系数的特征提取函数B-SIFT来定位病变区域。最后，定义了Bhattacharyya系数的两个病变特征，通过构造基于Bhattacharyya系数归一化的特征向量，获得基于B-SIFT的特征区域描述符。实验结果表明，该方法定位精度高，召回率高，能耗低，时间消耗低，比传统的病灶定位方法更有效，更可行。