Fetal-Brain-Segmentation

Introduction

This repository contains the implementation of 2D UNet architecture for fetal brain segmentation

Network Architecture

(https://arxiv.org/pdf/1505.04597.pdf)

Raw data

First figure shows raw MR image, second hand annotated groundtruth image and last shows weight map for spatial weighted cross entropy loss

Results

Model predictions

Dice score with epochs

How to use?

git clone https://github.com/koriavinash1/Fetal-Brain-Segmentation.git
cd Fetal-Brain-Segmentation
pip install -r requirements.txt

Pre-Processing data

Run Generate_Procesed_Data notebook for generating pre-processed data

Folder structure

./src consists all source codes

config -> all initial configurations

data_loader -> multithread data loader

estimator -> model estimator class

network -> network architecture definition

runner -> main function

python runner.py for training and python predictor.py for testing the model

If any comments or issues, pull requests/issues are Welcomed....

Thankyou

Contact

• Avinash Kori ([email protected])