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Breast-Cancer-Diagnosis-CNN

Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning Methods (CNN)

PSOWNNs-CNN: A Computational Radiology for Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning Methods

https://www.hindawi.com/journals/cin/2022/5667264/

If you find our work useful in your research please consider citing our paper:

@article{nomani2022psownns,
  title={PSOWNNs-CNN: a computational radiology for breast cancer diagnosis improvement based on image processing using machine learning methods},
  author={Nomani, Ashkan and Ansari, Yasaman and Nasirpour, Mohammad Hossein and Masoumian, Armin and Pour, Ehsan Sadeghi and Valizadeh, Amin},
  journal={Computational Intelligence and Neuroscience},
  volume={2022},
  year={2022},
  publisher={Hindawi}
}

Description

This repository contains an implementation of a Convolutional Neural Network (CNN) for breast cancer detection. The BreastCancerCNN class is an object-oriented implementation of a CNN using TensorFlow 2. The model is trained on a dataset of breast cancer images and labels, and the trained model is evaluated on a separate test set. The goal of this project is to develop an accurate model for early breast cancer detection.

Installation

To use the BreastCancerCNN class, you will need to have the following packages installed:

  • TensorFlow 2
  • NumPy
  • scikit-learn

You can install these packages using the following command:

pip install -r requirements.txt

Usage

To use the BreastCancerCNN class, follow these steps:

Clone the repository to your local machine.

Download the breast cancer images and labels dataset and save them as 'breast_cancer_images.npy' and 'breast_cancer_labels.npy', respectively, in the repository's root directory.

Run the 'run.py' script to train and evaluate the model.

The 'run.py' script loads the dataset, trains the model, and evaluates its performance on a separate test set. To run the script, use the following command:

python run.py

Dataset

The breast cancer images and labels dataset is not included in this repository due to its large size. You can download the dataset from Kaggle or from other sources.

Results

Credits

The BreastCancerCNN class was developed by Armin Masoumian and is licensed under the MIT License.

References