/RBVS

Retina Blood Vessel Segmentation using R2U-Net on CHASEDB1 and DRIVE dataset

Primary LanguageJupyter Notebook

PyTorch Implementation of U-Net, R2U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation https://arxiv.org/abs/1505.04597

Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation https://arxiv.org/abs/1802.06955

Results

You can see the stable version and final results in Google Colab: https://colab.research.google.com/drive/1C16K0BN5W6dATF1ubeibTl8vXgb6MDFj?usp=sharing

image image

U-Net

image

R2U-Net

image

Evaluation

I tested the R2U-Net model with CHASEDB1 and DRIVE dataset. The dataset was split into three subsets: training set, validation set, and test set, which the proportion is 60%, 20% and 20% of the whole dataset, respectively.