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CISC471-882

Authors: Catarina Borges McDiarmid, Mide Olanrewaju & Shrinidhi Thatahngudi Sampath Krishnan

Description

CISC 471/882 final project on developing a binary cancer classification computer neural network (CNN) model to classify mediastinal lymph nodes using CT images.

Datasets

This project uses the images and segmentation data found in the following TCIA repository:

Pan-cancerous lymph node CTs with annotations:

https://www.cancerimagingarchive.net/collection/mediastinal-lymph-node-seg/

Imports/installations

This project uses Python and Anaconda.

You can install python at https://www.python.org/downloads/

You can install Anaconda at https://anaconda.org/

Anaconda environment setup

  • Open Anaconda Prompt
  • Create an environment using conda create --name <env-name> python==3.12.3
  • Activate the environment using conda activate <env-name>
  • Install required packages in the environment

Required Packages

To install all the required packages, run the following in your command line:

pip install -r requirements.txt

Individually, all the imports required are:

  • pydicom --> pip install pydicom
  • os --> standard library
  • cv2 --> pip install opencv-python
  • numpy --> pip install numpy
  • sklearn --> pip install scikit-learn
  • json --> standard library
  • tensorflow --> pip install tensorflow
  • keras --> pip install keras

Additional requirements

To run the program, you will need to copy the template_paths.json file on your computer and follow the instructions in the file.

License

Copyright (C) 2024 Catarina Borges McDiarmid, Mide Olanrewaju & Shrinidhi Thatahngudi Sampath Krishnan

See the LICENSE file for license rights and limitations (GNU General Public License v3.0)