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Code implemented in Python for the classification of MRI images from OASIS (https://www.kaggle.com/datasets/ninadaithal/imagesoasis). A CNN is used for multiclass image classification (with oversampling in one of the cases) and for binary classification.

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A code developed in Python is used for the classification of MRI images from a dataset sourced from OASIS obtained from Kaggle (https://www.kaggle.com/datasets/ninadaithal/imagesoasis). For classification, a CNN is constructed using keras, which has also been used in Kaggle code for this dataset (see link).

Classification

  • First, the images are processed to have a single black-and-white channel.

Two approaches are followed:

  • In the first approximation, for both binary and multiclass classification, the number of images from the class with the lowest number of images will be selected.
  • In the second approximation, for multiclass classification, oversampling will be performed using SMOTE.

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Code implemented in Python for the classification of MRI images from OASIS (https://www.kaggle.com/datasets/ninadaithal/imagesoasis). A CNN is used for multiclass image classification (with oversampling in one of the cases) and for binary classification.

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