Training 3D CNN models
Version 1.0.0 (5.53 KB) by
Amir Ebrahimi
This code can be used in conjunction with some 3D CNN models for classification.
Use 'MRI_ADvsNC' to train a 3D CNN with your data. This code was originaly used for Alzheimer's disease detection using MRI for two classes. In the code, you can change the number of classes and the type of input data.
Some 3D CNN models can be found here:
3D ResNet-18: https://au.mathworks.com/matlabcentral/fileexchange/82585-pre-trained-3d-resnet-18?s_tid=prof_contriblnk
3D ResNet-50: https://au.mathworks.com/matlabcentral/fileexchange/87427-pre-trained-3d-resnet-50?s_tid=prof_contriblnk
3D ResNet-101: https://au.mathworks.com/matlabcentral/fileexchange/87432-pre-trained-3d-resnet-101?s_tid=prof_contriblnk
3D LeNet-5: https://au.mathworks.com/matlabcentral/fileexchange/87442-pre-trained-3d-lenet-5?s_tid=prof_contriblnk
Please cite the following paper if you find these models useful:
Cite As
Ebrahimi, Amir, et al. “Introducing Transfer Learning to 3D ResNet-18 for Alzheimer’s Disease Detection on MRI Images.” 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, 2020, doi:10.1109/ivcnz51579.2020.9290616.
MATLAB Release Compatibility
Created with
R2021a
Compatible with any release
Platform Compatibility
Windows macOS LinuxTags
Acknowledgements
Inspired by: Alzheimer’s Disease Detection using 3D ResNet-18 on MRI, Deep Learning: Transfer Learning in 10 lines of MATLAB Code, Deep Learning Tutorial Series, Deep Learning in 11 Lines of MATLAB Code
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Version | Published | Release Notes | |
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1.0.0 |