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

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Results

Model predictions

Dice score with epochs

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How to use?

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

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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

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

Thankyou

Contact

• Avinash Kori (avinashgkori@smail.iitm.ac.in)