Breast density classification with deep convolutional neural networks

Introduction

This is an implementation of the model used for breast density classification as described in our paper "Breast density classification with deep convolutional neural networks". The implementation allows users to get the breast density prediction by applying one of our pretrained models: a histogram-based model or a multi-view CNN. Both models act on screening mammography exams with four standard views. As a part of this repository, we provide a sample exam (in images directory).

Prerequisites

Python (3.6), TensorFlow (1.5.0), NumPy (1.14.3), SciPy (1.0.0).
NVIDIA GPU (we used Tesla M40).

Data

To use one of the pretrained models, the input is required to consist of four images, one for each view (L-CC, L-MLO, R-CC, R-MLO). Each image has to have the size of 2600x2000 pixels. The images in the provided sample exam were already cropped to the correct size.

How to run the code

Available options can be found at the bottom of the file density_model.py. You can set the model to 'cnn' or 'histogram'. Please keep input_size = (2600, 2000) as the provided pretrained models were trained with images in this resolution. You may need to change gpu_number.

Run the following command to use the model.

python density_model.py

You should get the following outputs for the sample exam provided in the repository.

With model = 'histogram':

Density prediction:
        Almost entirely fatty (0):                      0.08194443
        Scattered areas of fibroglandular density (1):  0.7830397
        Heterogeneously dense (2):                      0.13350312
        Extremely dense (3):                            0.0015126525

With model = 'cnn':

Density prediction:
        Almost entirely fatty (0):                      0.20968862
        Scattered areas of fibroglandular density (1):  0.7650766
        Heterogeneously dense (2):                      0.024949048
        Extremely dense (3):                            0.0002858529

Reference

If you found this code useful, please cite our paper:

Breast density classification with deep convolutional neural networks
Nan Wu, Krzysztof J. Geras, Yiqiu Shen, Jingyi Su, S. Gene Kim, Eric Kim, Stacey Wolfson, Linda Moy, Kyunghyun Cho
ICASSP, 2018

@inproceedings{breast_density,
    title = {Breast density classification with deep convolutional neural networks},
    author = {Nan Wu and Krzysztof J. Geras and Yiqiu Shen and Jingyi Su and S. Gene Kim and Eric Kim and Stacey Wolfson and Linda Moy and Kyunghyun Cho},
    booktitle = {ICASSP},
    year = {2018}
}