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Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers

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Automated-Cardiac-Segmentation-and-Disease-Diagnosis

Introduction

This repository contains the implementation for automated cardiac segmentation and diasease classification introduced in the following paper: "Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers" (https://arxiv.org/abs/1801.05173)

Citation

If you find this implementation useful in your research, please consider citing:

@article{khened2018fully,
  title={Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers},
  author={Khened, Mahendra and Kollerathu, Varghese Alex and Krishnamurthi, Ganapathy},
  journal={arXiv preprint arXiv:1801.05173},
  year={2018}
}

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Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers

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