This example shows how to work with an MRI brain image dataset and how to use transfer learning to modify and retrain ResNet-18, a pretrained convolutional neural network, to perform image classification on that dataset.
The MRI scans used in this example were obtained during a study  of social brain development conducted by researchers at the Massachussets Institute of Technology (MIT), and are available for download via the OpenNEURO platform: https://openneuro.org/datasets/ds000228/versions/1.1.0
This example uses the horizontal midslice images from the brain MRI scan volumes and classifies them into 3 categories according to the chronological age of the participant:
- Participants Aged 3-5
- Participants Aged 7-12
- Participants older than 18, classified as Adults
- Exploring a public brain MRI image dataset
- Preparing the dataset for deep learning
- Training a deep learning model to perform chronological age classification
- Evaluating the trained model
To run on your local machine or cloud instance, open & run the live script
 Richardson, H., Lisandrelli, G., Riobueno-Naylor, A., & Saxe, R. (2018). Development of the social brain from age three to twelve years. Nature Communications, 9(1), 1027. https://doi.org/10.1038/s41467-018-03399-2
Copyright 2020 The MathWorks, Inc.
Vijay Iyer (2023). Brain-MRI-Age-Classification-using-Deep-Learning (https://github.com/matlab-deep-learning/Brain-MRI-Age-Classification-using-Deep-Learning/releases/tag/v1.1), GitHub. 检索来源 .
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无法下载基于 GitHub 默认分支的版本
See release notes for this release on GitHub: https://github.com/matlab-deep-learning/Brain-MRI-Age-Classification-using-Deep-Learning/releases/tag/v1.1
See release notes for this release on GitHub: https://github.com/matlab-deep-learning/Brain-MRI-Age-Classification-using-Deep-Learning/releases/tag/v1.0.1
Add a modified version of main Live Script for rendering purposes