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Morphological prognosis prediction of choroid neovascularization from longitudinal SD‐OCT images by Jiayan Shen; Zhongyue Chen; Yuanyuan Peng; Siqi Zhang; Chenan Xu; Weifang Zhu; Haiyun Liu; Xinjian Chen is a Medicine article available to read on EtoBox.

What is Morphological prognosis prediction of choroid neovascularization from longitudinal SD‐OCT images about?

Background: Choroid neovascularization (CNV) has no obvious symptoms in the early stage, but with its gradual expansion, leakage, rupture, and bleeding, it can cause vision loss and central scotoma. In some severe cases, it will lead to permanent visual impairment. Purpose: Accurate prediction of disease progression can greatly help ophthalmologists to formulate appropriate treatment plans and prevent further deterioration of the disease. Therefore, we aim to predict the growth trend of CNV to help the attending physician judge the effectiveness of treatment. Methods: In this paper, we develop a CNN-based method for CNV growth prediction. To achieve this, we first design a registration network to rigidly register the spectral domain optical coherence tomography (SD-OCT) B-scans of each subject at different time points to eliminate retinal displacements of longitudinal data. Then, considering the correlation of longitudinal data, we propose a co-segmentation network with a correlation attention guidance (CAG) module to cooperatively segment CNV lesions of a group of follow-up images and use them as input for growth prediction. Finally, based on the above registration and segmentatio

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Author

Jiayan Shen; Zhongyue Chen; Yuanyuan Peng; Siqi Zhang; Chenan Xu; Weifang Zhu; Haiyun Liu; Xinjian Chen

Publisher

Wiley

Published

2023

Language

EN

Field

Medicine (Health Sciences)