Target region segmentation method and system of ultrasonic image and electronic equipment

The invention discloses a target area segmentation method and system for an ultrasonic image and electronic equipment, and relates to the technical field of image processing. The method comprises the steps of obtaining a to-be-measured ultrasonic image; inputting a to-be-detected ultrasonic image into the full-scale convolutional neural network model to obtain a target region segmentation result; the full-scale convolutional neural network model is obtained by training an initial full-scale convolutional neural network model by using a joint loss function according to the enhanced historical target ultrasonic image set. According to the method, the initial full-scale convolutional neural network model is constructed and trained, so that the segmentation precision of the target region of the ultrasonic image can be improved. 本发明公开了一种超声影像的目标区域分割方法、系统及电子设备，涉及图像处理技术领域。方法包括：获取待测超声影像；将待测超声影像输入到全尺度卷积神经网络模型中，得到目标区域分割结果；全尺度卷积神经网络模型是根据增强处理后的历史目标超声影像集，利用联合损失函数对初始全尺度卷积神经网络模型进行训练后得到的。本发明通过构建并训练初始全尺度卷积神经网络模型，能够提高超声影像目标区域分割