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This is the Pytorch implementation of the paper in Journal of Periodontology "Construction of an end-to-end regression neural network for the determination of a quantitative index sagittal root inclination". https://aap.onlinelibrary.wiley.com/doi/10.1002/JPER.21-0492

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teeth_angle

This is the Pytorch&Python3 implementation of the paper "Construction of an end-to-end regression neural network for the determination of a quantitative index sagittal root inclination" (https://aap.onlinelibrary.wiley.com/doi/10.1002/JPER.21-0492), which was published ion Jan 2022.

To cite the paper,

Lin Y, Shi M, Xiang D, Zeng P, Gong Z, Liu H, Liu Q, Chen Z, Xia J, Chen Z. Construction of an end-to-end regression neural network for the determination of a quantitative index sagittal root inclination. J Periodontol. 2022 Feb 12. doi: 10.1002/JPER.21-0492. Epub ahead of print. PMID: 35150132.

Required packages: Pytorch, Numpy, Pandas, torchvision.

To run the code, please use: python3 train.py

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This is the Pytorch implementation of the paper in Journal of Periodontology "Construction of an end-to-end regression neural network for the determination of a quantitative index sagittal root inclination". https://aap.onlinelibrary.wiley.com/doi/10.1002/JPER.21-0492

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