Deep Learning Model based Semantic Segmentation Network for Ultrasound Gallballder Images

In this paper, automated deep learning model is discussed for the segmentation of images using semantic segmentation network. In this process different types of data sets are used to train the network and the model is tested with the ultrasound gall bladder images and parameters such as accuracy, sensitivity is calculated. Comparing with the existing methods, proposed method improves the segmentation accuracy more than 5%.