In the medical ultrasonic imaging technology, factors such as the imaging equipment, imaging mechanism, and non-uniformity of detection objects lead to problems of speckle noise and partial distortion in ultrasonic images, which not only reduce the quality of ultrasonic images, but also increase the difficulty of clinical diagnosis. In order to effectively suppress speckle noise in ultrasonic images, this paper proposes an adaptive bilateral filtering denoising method for ultrasonic images based on BP (back propagation) neural network. According to the similarity value between the local region and reference noise region predicted by BP neural network, our method can distinguish the noise regions and the tissue regions in the ultrasonic image. After that, the similarity value predicted by the BP neural network is combined with a bilateral filter to realize adaptive filtering of the ultrasonic images, and the bilateral filter can perform different filtering for different regions of the ultrasonic image. Experiments are carried out based on four ultrasonic images (the physical phantom ultrasonic image, the liver ultrasonic image 1, the liver ultrasonic image 2, and the kidney ultrasonic image). The results show that the method can better suppress speckle noise in the ultrasonic image and preserve its edge features, and can also obtain higher signal-to-noise ratio and better visual effect.