In recent years, deep learning based methods have shown success in essential medical image analysis tasks such as segmentation. Post-processing and refining the results of segmentation is a common practice to decrease misclassifications originating from network. addition widely used like Conditional Random Fields (CRFs) which focus on structure segmented volume/area, graph-based approach makes ...

Interactive single-image segmentation is ubiquitous in the scientific and commercial imaging software. Lightweight neural network one practical effective way to accomplish task. This work focuses on problem only with some seeds such as scribbles. Inspired by dynamic receptive field human being’s visual system, we propose Gaussian convolution (GDC) fast efficiently aggregate contextual informati...