Prediction of 3D Strain Field in Posterior Sclera Based on Attention 3D U-Net_Vol. 2 No. 3 (JBDC 2024)_Journal of Big Data and Computing (ISSN: 2959-0590)

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Prediction of 3D Strain Field in Posterior Sclera Based on Attention 3D U-Net

DOI: https://doi.org/10.62517/jbdc.202401322

Author(s)

Xubo Zhang1,*, Yusong Wang1,*, Siyuan Shao1, Chongbao Zhou1, Mingming Gong2

Affiliation(s)

1School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, Henan, 450001, China 2iFLYTEK Co., Ltd., Hefei, Anhui, 230088, China *Corresponding Author.

Abstract

To analyze the biomechanical properties of the posterior sclera, we denoised OCT images and segmented them using the nnU-Net model. After obtaining the segmented tissues, we performed registration and calculated the deformation of the posterior eye tissues using mathematical methods. Finally, we combined the baseline images and the force-loaded images and trained an Attention 3D U-Net model to predict the deformation of the posterior sclera, i.e., to predict its 3D strain field. The model performance was evaluated using the mean absolute error (MAE), which was below 0.2.

Keywords

Posterior Sclera; 3D Strain Field; Attention Mechanism; 3D U-Net; Deep Learning

References

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