버전 1.1 (71.6 MB) 작성자: Vijay Iyer
MATLAB example using deep learning to classify chronological age from brain MRI images

다운로드 수: 947

업데이트 날짜: 2021/1/19

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Brain MRI Age Classification Using Deep Learning

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 [1] of social brain development conducted by researchers at the Massachussets Institute of Technology (MIT), and are available for download via the OpenNEURO platform:

This example shows how horizontal midslice images from the brain MRI scan volumes can be classified into 3 categories according to the chronological age of the participant:

  1. Participants Aged 3-5
  2. Participants Aged 7-12
  3. Participants older than 18, classified as Adults

This example works though multiple steps of a deep learning workflow:

  • 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

Running the Example

Open and run the live script BrainMRIAgeClassificationUsingDeepLearning.mlx



[1] 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.

Copyright 2020 The MathWorks, Inc.

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인용 양식

Vijay Iyer (2023). Brain-MRI-Age-Classification-using-Deep-Learning (, GitHub. 검색됨 .

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