Abstract: Aiming at the problems of  texture blurring such as speckle noise, region blurring, and weak boundaries in the image caused  by factors such as noise and artifacts during utrasound imaging,  which led to a decrease in the quality of ultrasound image segmentation, we proposed  an ultrasound image segmentation algorithm based on improved attention W-Net. Firstly, we constructed texture feature factors based on the correlation between pixel intensity and edge texture, and applied texture factors to improve the guided filtering algorithm. The improved guided filtering algorithm could smooth the image while better preserving the texture features in the image. Secondly, by extending U-Net to W-Net through attention mechanism, an improved attention mechanism was integrated into W-Net. The improved attention W-Net was used to segment ultrasound images with texture preservation, which could better preserve the texture information of the image during the segmentation process, thereby improving the accuracy and robustness of segmentation. Experimental results show that the proposed method has a relatively high cumulative probability of blur detection (CPBD) value, a low percentage of area difference, and good ultrasound image segmentation effect, which can be widely applied in the field of ultrasound image segmentation.

Key words: improved attention W-Net, ultrasound image, division, texture factor, improved , guidance filtering algorithm