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Quality Assessment tool for fetal brain MRIs, able to score each volume through a deep learning regression model. Developed using Python3 and Keras/Tensorflow framework.

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ilegorreta/Automatic-Fetal-Brain-Quality-Assessment-Tool

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Automatic Fetal Brain Quality Assessment

Developed by Iván Legorreta

Contact info: [email protected]


The aim of this project was to develop a Quality Assessment tool for fetal brain MRIs, which is able to score each volume through a deep learning regression model. Developed using Python3 and Keras/Tensorflow framework.

Our network architecture consists of a non-linear configuration, known as Residual Network (ResNet) architecture: Resnet Architecture Diagram

Given that we are dealing with an unbalanced distribution regarding input dataset, we applied different weights to each input class to compensate for the imbalance in the training sample.


Requirements

  • Linux environment
  • Python3
  • Conda/Anaconda setup

Installation

  1. Create the environment from the conda_environment.yml file:
  conda env create -f conda_environment.yml

The first line of the yml file sets the new environment's name.

  1. Activate the new environment: conda activate myenv

  2. Verify that the new environment was installed correctly:

  conda env list

You can also use conda info --envs

For more information, visit Conda documentation.

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Quality Assessment tool for fetal brain MRIs, able to score each volume through a deep learning regression model. Developed using Python3 and Keras/Tensorflow framework.

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