https://github.com/sadmansakib93/medical_image_classification_keras

This is an example of medical image classification (binary classification) using Keras. Note that, the model is not fully optimized in this program, and hence it can be further optimized and the accuracy of the model can be enhanced further.
https://github.com/sadmansakib93/medical_image_classification_keras

convolutional-neural-networks deep-learning deep-neural-networks image-classification keras keras-neural-networks machine-learning medical-image-analysis

Last synced: 3 months ago
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This is an example of medical image classification (binary classification) using Keras. Note that, the model is not fully optimized in this program, and hence it can be further optimized and the accuracy of the model can be enhanced further.

• Host: GitHub
• URL: https://github.com/sadmansakib93/medical_image_classification_keras
• Owner: SadmanSakib93
• Created: 2020-07-16T03:01:11.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-07-16T03:21:46.000Z (almost 5 years ago)
• Last Synced: 2025-01-12T01:22:26.817Z (5 months ago)
• Topics: convolutional-neural-networks, deep-learning, deep-neural-networks, image-classification, keras, keras-neural-networks, machine-learning, medical-image-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 37.1 KB
• Stars: 4
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Medical Image Classification Keras (Binary classification)

* Download the dataset: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia

* Store the downloaded dataset in a folder named "DS2" (or you can name whatever you want it, in that case change root folder inside the program accordingly)

* Inside the DS2 folder, put the train dataset into a folder named "train", put the validation data into a folder named "validation", and the test data inside a folder named "test". 

* In this dataset, we have two classes: Normal, and Pneumonia

* The structure of your dataset folder (i.e., DS2) should be as follows:

#DS2

    - train

    

        -NORMAL

        

        -PNEUMONIA

        

    - validation

    

         -NORMAL

         

         -PNEUMONIA

         

    - test

    

         -NORMAL

         

         -PNEUMONIA

         

         

 * Now run the program.