Pre-trained 3D LeNet-5

Versione 1.0.1 (277 KB) da Amir Ebrahimi

Pre-trained Neural Network Toolbox Model for 3D LeNet-5 Network

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Aggiornato 6 mag 2021

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Our implementation of 2D LeNet-5 model achieved 98.48% accuracy on the grey-scale MNIST test set after training on its train set. To transfer the learnable parameters from pre-trained 2D LeNet-5 (MNIST) 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 LeNet-5 learns patterns in each frame. This model has about 260,000 learnable parameters.

simply, call "lenet5TL3Dfun()" function.

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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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Creato con R2020b

Compatibile con R2019b e release successive

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Ispirato da: Deep Learning Network Analyzer for Neural Network Toolbox, Pre-trained 2D LeNet-5

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lenet5TL3Dfun.mlx

Versione	Pubblicato	Note della release
1.0.1	6 mag 2021	The relevant paper is published.	Zip Toolbox
1.0.0	16 feb 2021		Toolbox Zip

MLA	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.
APA	Ebrahimi, A., Luo, S., & Alzheimer’s Disease Neuroimaging Initiative, for the. (2021). Convolutional neural networks for Alzheimer’s disease detection on MRI images. Journal of Medical Imaging, 8(02). SPIE-Intl Soc Optical Eng. Retrieved from https://doi.org/10.1117%2F1.jmi.8.2.024503
BibTeX	@article{Ebrahimi_2021, doi = {10.1117/1.jmi.8.2.024503}, url = {https://doi.org/10.1117%2F1.jmi.8.2.024503}, year = 2021, month = {apr}, publisher = {{SPIE}-Intl Soc Optical Eng}, volume = {8}, number = {02}, author = {Amir Ebrahimi and Suhuai Luo and for the Alzheimer's Disease Neuroimaging Initiative}, title = {Convolutional neural networks for Alzheimer's disease detection on {MRI} images}, journal = {Journal of Medical Imaging} }