Acute branch retinal artery occlusion segmentation based on Bayes posterior probability and deep learning

Chao Guo; Weifang Zhu; Meng Wang; Ming Liu; Zhongyue Chen; Xinjian Chen

doi:10.1117/12.2611500

4 April 2022 Acute branch retinal artery occlusion segmentation based on Bayes posterior probability and deep learning

Chao Guo, Weifang Zhu, Meng Wang, Ming Liu, Zhongyue Chen, Xinjian Chen

Proceedings Volume 12032, Medical Imaging 2022: Image Processing; 120323V (2022) https://doi.org/10.1117/12.2611500
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

Branch retinal artery occlusion (BRAO) is an ophthalmic emergency. Acute BRAO is a clinical manifestation of BRAO. Due to its various shapes, locations and the blurred boundary, the automatic segmentation of acute BRAO is very challenging. To tackle these problems, we propose a novel method based on deep learning for automatic acute BRAO segmentation in optical coherence tomography (OCT) image. In this method, a novel Bayes posterior attention network, named as BPANet, is proposed for precise segmentation of the lesion. Our major contributions include: (1) A novel Bayes posterior probability based spatial attention module is used to enhance the information of lesion region. (2) An effective max-pooling and average-pooling channel attention module is embedded into BPANet to improve the effectiveness of the feature extraction. The proposed method is evaluated on 472 OCT B-scan images with a 4-fold cross validation strategy. The mean and standard deviation of Dice similarity coefficient, true positive rate, accuracy and intersection over union are 85.48±1.75%, 88.84±1.19%, 98.63±0.48% and 76.88±2.92%, respectively. The primary results show the effectiveness of the proposed method.

Conference Presentation

Citation Download Citation

Chao Guo, Weifang Zhu, Meng Wang, Ming Liu, Zhongyue Chen, and Xinjian Chen "Acute branch retinal artery occlusion segmentation based on Bayes posterior probability and deep learning", Proc. SPIE 12032, Medical Imaging 2022: Image Processing, 120323V (4 April 2022); https://doi.org/10.1117/12.2611500

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