Pre-trained 3D ResNet-18

Pre-trained Neural Network Toolbox Model for 3D ResNet-18 Network
Updated 6 May 2021

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To transfer the learnable parameters from pre-trained 2D ResNet-18 (ImageNet) to 3D one, we duplicated 2D filters (copying them repeatedly) through the third dimension. This is possible since a video or a 3D image can be converted into a sequence of image slices. In the training process, we expect that the 3D ResNet-18 learns patterns in each frame. This model has 34 million learnable parameters.

simply, call "resnet18TL3Dfunction()" function.

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.

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Ebrahimi, Amir, et al. “Convolutional Neural Networks for Alzheimer’s Disease Detection on MRI Images.” Journal of Medical Imaging, vol. 8, no. 02, SPIE-Intl Soc Optical Eng, Apr. 2021, doi:10.1117/1.jmi.8.2.024503.

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MATLAB Release Compatibility
Created with R2020b
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

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