scholarly journals Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography

2021 ◽  
Vol 11 (12) ◽  
pp. 5488
Author(s):  
Wei Ping Hsia ◽  
Siu Lun Tse ◽  
Chia Jen Chang ◽  
Yu Len Huang

The purpose of this article is to evaluate the accuracy of the optical coherence tomography (OCT) measurement of choroidal thickness in healthy eyes using a deep-learning method with the Mask R-CNN model. Thirty EDI-OCT of thirty patients were enrolled. A mask region-based convolutional neural network (Mask R-CNN) model composed of deep residual network (ResNet) and feature pyramid networks (FPNs) with standard convolution and fully connected heads for mask and box prediction, respectively, was used to automatically depict the choroid layer. The average choroidal thickness and subfoveal choroidal thickness were measured. The results of this study showed that ResNet 50 layers deep (R50) model and ResNet 101 layers deep (R101). R101 U R50 (OR model) demonstrated the best accuracy with an average error of 4.85 pixels and 4.86 pixels, respectively. The R101 ∩ R50 (AND model) took the least time with an average execution time of 4.6 s. Mask-RCNN models showed a good prediction rate of choroidal layer with accuracy rates of 90% and 89.9% for average choroidal thickness and average subfoveal choroidal thickness, respectively. In conclusion, the deep-learning method using the Mask-RCNN model provides a faster and accurate measurement of choroidal thickness. Comparing with manual delineation, it provides better effectiveness, which is feasible for clinical application and larger scale of research on choroid.

2020 ◽  
Vol Volume 14 ◽  
pp. 2265-2270
Author(s):  
Yousef Ahmed Fouad ◽  
Abdelrahman Gaber Salman ◽  
Thanaa Helmy Mohamed ◽  
Randa Hesham Ali Abdelgawad ◽  
Samah Ibraheem Hassen

2015 ◽  
Vol 233 (3-4) ◽  
pp. 204-208 ◽  
Author(s):  
Ece Turan-Vural ◽  
Nursal Yenerel ◽  
Murat Okutucu ◽  
Elvin Yildiz ◽  
Nejla Dikmen

Background/Aim: Pseudoexfoliation (PSX) syndrome is associated with blood flow disturbances; however, its exact effect on choroidal blood flow and thickness remains to be elucidated. This study compared subfoveal choroidal thickness in normal eyes and in eyes with PSX using enhanced depth imaging optical coherence tomography (EDI-OCT). Methods: This prospective, cross-sectional study included 35 eyes of 35 patients (20 males, 15 females) with unilateral or bilateral PSX and 26 eyes of 26 healthy volunteers (13 males, 13 females). Besides a comprehensive ocular and physical examination, all subjects underwent EDI-OCT examination using an Optovue RTVue OCT device (Optovue Inc., Fremont, Calif., USA). Results: The mean choroidal thickness (CT) and ocular perfusion pressure (OPP) were lower in the PSX group than in the healthy controls (249.4 ± 46.3 vs. 282.5 ± 55.8 µm, p = 0.014 and 40.7 ± 5.8 vs. 44.3 ± 4.3 mm Hg, p = 0.007, respectively). In addition, both systolic blood pressure and diastolic blood pressure measurements were lower among the PSX patients. However, no correlation was found between CT and OPP. Conclusion: The findings of this study suggest that PSX is associated with an overall thinning of the subfoveal choroid and a significant decrease in OPP. Future studies are warranted to further examine these relations.


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