The learning-to-read from ahsanp

learning-to-read's Introduction

Learning to Read Chest X-Rays

Source code for the CVPR 2016 paper:

Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation (arxiv)

The source code is based on the:

cifar.torch by Sergey Zagoruyko, for the CNN training
char-rnn by Andrej Karpathy, for the RNN training

The overall pipeline and codes for preparing data, training, and sampling can be found in the src/chestx

Dataset can be downloaded from the Open-i chest x-ray subset (link)

Trained models can be downloaded:

CNN - GoogLeNet model
RNN-LSTM, RNN-GRU

Required software packages:

Torch
Python 2.7 with the following packages:
- Numpy
- Matplotlib
- Pandas
- Scikit-Learn
- Scikit-Image
- iPython Notebook - Optional
- NLTK - Optional

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