Training 3D CNN models
Versión 1.0.0 (5,53 KB) por
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:
Citar como
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.
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R2021a
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Inspirado por: 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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Versión | Publicado | Notas de la versión | |
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1.0.0 |