Final Project Group 9: Diabetic Retinopathy Detection: Identifying the Severity of Diabetic Retinopathy in Eye Images
Brent Garey, Kelly Ly, Ann Men, Bishoy Sargius, and William Zouzas
COMP.4600/5300 Computing for Health and Medicine
4/26/2022
https://github.com/lykelly19/Computing-for-Health-and-Medicine-Final
Our goal was to create a model to efficiently and accurately detect the severity of DR in eye images to avoid manual classification by clinicians. We were able to pre-process, augment and split eye images into 4 quadrants. We created Quadrant Based Ensemble Inception V3 (instead of V2) models for each quadrant. We trained and tested the model to detect the severity of DR in eye images.
Source used for dataset: [1] "Diabetic Retinopathy Detection." https://www.kaggle.com/competitions/diabetic-retinopathy-detection/ (accessed April 4, 2022).
Source used for implementation method using Quadrant Based Ensemble Inception: [2] C. Bhardwaj, S. Jain, and M. Sood, "Deep Learning-Based Diabetic Retinopathy Severity Grading System Employing Quadrant Ensemble Model," (in eng), J Digit Imaging, vol. 34, no. 2, pp. 440-457, Apr 2021, doi: 10.1007/s10278-021-00418-5.
- Matplotlib
- Pandas
- Pillow
- NumPy
- OS
- Shutil
- Random
- Imutils
- Seaborn
- Statistics
- Keras
- Tensorflow
- PyTorch
- Torchvision
- opencv-python
- imutils
data/ |_labeled_data/ |_0/ |_1/ |_2/ |_3/ |_4/ |_normalized_whole_images/ |_0/ |_1/ |_2/ |_3/ |_4/ |_quadrants/ |_quadrant_1/ |_0/ |_1/ |_2/ |_3/ |_4/ |_quadrant_2/ |_0/ |_1/ |_2/ |_3/ |_4/ |_quadrant_3/ |_0/ |_1/ |_2/ |_3/ |_4/ |_quadrant_4/ |_0/ |_1/ |_2/ |_3/ |_4/
Open the “DR Detection Group 9.ipynb” file using Jupyter Notebook. Click on Cell > Run All.