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Multi-class image classifier for medical fundus images

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Introduction

Multi-class image classifer for Fundus Opthamologic Medical Imagings

Detects the following disease:

  • Normal
  • Diabetic Retinopathy
  • Cataract
  • Glaucoma
  • Age Related Macular Degeneration
  • Patholical Myopia

Accuracy = .74

Confusion Matrix

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ROC

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Model Accuracy and Loss

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Using model

from keras.models import Model, load_model
model= load_model(PATH/model.h5)

Demo to come

How to Run and Train Model Locally

training_model.ipynb

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Download Jupyter Notebooks, Anaconda, Python 3

https://jupyter.org/install

https://www.anaconda.com/products/individual

https://www.python.org/downloads/

Have the following Python Libraries Installed

  • numpy
  • pandas
  • cv2
  • matplotlib
  • Tensorflow 2
  • Keras
  • IPython
  • PIL
  • sklearn
  • itertools

The model was trained and created in AWS Sagemaker. Please note comments to make changes to run locally.

Examples of GradCam Images

Normal Image

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Diabetic Retinopathy Image

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Glaucoma Image

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Website

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Data

Source Diease
https://www.kaggle.com/jr2ngb/cataractdataset Cataracts, Glaucoma
https://www.kaggle.com/linchundan/fundusimage1000 Myopia, AMD
https://www.kaggle.com/nguyenhung1903/diaretdb1-v21 Diabetic Retinopathy
http://www5.informatik.uni-erlangen.de/research/data/fundus-images/ Diabetic Retinopathy, Glaucoma
https://www.it.lut.fi/project/imageret/diaretdb0/#DOWNLOAD Diabetic Retinopathy
https://personalpages.manchester.ac.uk/staff/niall.p.mcloughlin/ Glaucoma, Diabetic Retinopathy, AMD
https://ai.baidu.com/broad/download AMD, Glaucoma, Myopia
https://www.kaggle.com/andrewmvd/ocular-disease-recognition-odir5k Diabetic Retinopathy, Normal, Cataract, Glaucoma, AMD, Myopia
Logo Design- Jody Serani

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