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Fully automatic technique for fetal brain segmentation using deep convolutional neural network

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koriavinash1/Fetal-Brain-Segmentation

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Fetal-Brain-Segmentation

Introduction

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

Network Architecture

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

Raw data

data


Results

Model predictions

prediction

Dice score with epochs

dice


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


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

Thankyou python runner.py for training or testing the model