Before revision:  NEW FINDINGS: We introduce a new deep neural network architecture, the Focus U-Net , which achieves state-of-the-art performance for polyp segmentationacross five public datasets containing images of polyps obtained during colonoscopy.
After revision:  NEW FINDINGS: We introduce a new deep neural network architecture, the Focus U-Net , which combines efficient spatial and channel-based attention into a single Focus Gate module to encourage selective learning of polyp features. The Focus U-Net further incorporates short-range skip connections and deep supervision. Furthermore, we introduce the Hybrid Focal loss, a new compound loss function based on the Focal loss and Focal Tversky loss, to handle class-imbalanced image segmentation. For our experiments, we selected five public datasets containing images of polyps obtained during colonoscopy.