/Breast-Cancer-Classification

Primary LanguageJupyter Notebook

Breast-Cancer-Classification

The project is designed to diagnose of breast cancer using mammogram images. The classifier is attainalbe by using nerual networks and transfer learning. This implementation allows users to get breast cancer predition by applying our models to an input image.

Getting Started

Download python 3 on the computer and download the code and packages listed below to your local machine to setup the model

Prerequisites

Python Jupyter Notebook Numpy Pandas Matplotlib Pytorch torchvision SciPy

Installing

First to install python 3 onto your computer

Then to install all the packages needed to run the programs

pip install numpy pandas matplotlib Pytorch torchvision scipy jupyter notebook

Running the tests

The test consistes of several steps

  1. data clearning and create data loader
  2. apply filters to the input images
  3. run classifier
  4. run the model and get the results

Break down into end to end tests

The model is able to reach a validation accuracy of a%, precision a, recall a.

And coding style tests

Explain what these tests test and why

Give an example

Deployment

This model can make prediction about the input picture is either benign tumor or malignant tumor

Built With

  • Dropwizard - The web framework used
  • Maven - Dependency Management
  • ROME - Used to generate RSS Feeds

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

Acknowledgments

  • Hat tip to anyone whose code was used
  • Inspiration
  • etc