MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation

This repository contains the implementation of "MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation" in pytorch.

Paper

Ibtehaz, Nabil, and M. Sohel Rahman. "MultiResUNet: Rethinking the U-Net architecture for multimodal biomedical image segmentation." Neural Networks 121 (2020): 74-87.

• Read the Paper
• Original keras(tensorflow backend) implementation

Usage

from multiresunet import MultiResUnet 

net = MultiResUnet(channels=3,filters=16,nclasses=1)





"""
Arguments : 

channels - input image channels
filters - filters to begin with (Unet)
nclasses - number of classes
"""

• Dataset - TGS Salt Identification Challenge

Results

Trained on TGS Salt Identification Challenge data for 100 epochs