Context Axial Reverse Attention Network for Small Medical Objects Segmentation
CaraNet
CaraNet: Context Axial Reverse Attention Network for Small Medical Objects Segmentation
This repository contains the implementation of a novel attention based network (CaraNet) to segment the polyp (CVC-T, CVC-ClinicDB, CVC-ColonDB, ETIS and Kvasir) and brain tumor (BraTS). The CaraNet show great overall segmentation performance (mean dice) on polyp and brain tumor, but also show great performance on small medical objects (small polyps and brain tumors) segmentation.
The technique report is here: CaraNet
Architecture of CaraNet
Backbone
We use Res2Net as our backbone.
Context module
We choose our CFP module as context module, and choose the dilation rate is 8. For the details of CFP module you can find here: CFPNet. The architecture of CFP module as shown in following figure:
