Comparison of Unet architectures for segmentation of the left ventricle endocardial border on two-dimensional ultrasound images

Abstract

In this paper, we compare common Unet architectures with upgrade version Unet++ for segmentation of the the left ventricular (LV) endocardial boundaries on ultrasound images, which were obtained by ultrasound studies of the heart. The key difference of Unet++ from Unet is the improved skip connections between encoder and decoder by adding convolution blocks. Such implementation allows us to transfer information from encoder to decoder with avoiding to loss of small details of the ultrasound image. It is very important to detect internal boundaries accuratly. We evaluated Unet++ in comparison Unet and wide Unet. The Dice coefficient for the LV segmentation with Unet++ is 91.20%. This result of Unet++ for the LV area segmentation outperforms Unet and wide Unet architectures.