| Presentation preference | Oral presentation |
| Title | Automated vitreous haze grading using ultrawide-field fundus photographs and deep learning |
| Purpose | To evaluate the performance of a deep learning algorithm for the automated grading of vitritis on ultra-wide field imaging. |
| Methods | Ultra-wide field (UWF) fundus retinophotographs (Optos®, Dunfermline, United Kingdom) of patients followed for intermediate, posterior or pan-uveitis were used. Vitreous haze was defined on each UWF picture by two blinded experts according to the 6 steps of the Nussenblatt scale. Included images were automatically classified using the Inception V3 convolutional neural network from Google (California, USA). Images were fed to the model as follows: training (70%), validation (15%), and testing set (15%). The performance was assessed on the unused testing set. |
| Results | A total of 1181 images from 443 patients were included. The performance of the model for the detection of vitritis was good with a sensitivity of 96% (95% CI: 0.89-0.98) and a specificity of 87% (95% CI: 0.78-0.89). The area under the ROC curve was 0.92 (95% CI: 0.78-0.99). For the classification of vitritis into 6 classes, the global accuracy of the model was 64% increasing to 85% when accepting a maximum error margin of one class (95% CI: 0.76-0.94). |
| Conclusion | We describe a new deep learning model based on UWF fundus imaging that produces an automated tool for the detection and grading of vitreous haze with a good performance. |
| Conflict of interest | No |
Authors 1
| Last name | TOUHAMI |
| Initials of first name(s) | S |
| Department | Ophthalmology |
| City | Paris |
| Country | France |
Authors 2
| Last name | Mhibik |
| Initials of first name(s) | B |
| Department | Ophthalmology |
| City | Paris |
| Country | France |
Authors 3
| Last name | Bchir |
| Initials of first name(s) | C |
| Department | Biostatistics |
| City | Paris |
| Country | France |
Authors 4
| Last name | Gulic |
| Initials of first name(s) | K |
| Department | Ophthalmology |
| City | Paris |
| Country | France |
Authors 5
| Last name | Bodaghi |
| Initials of first name(s) | B |
| Department | Ophthalmology |
| City | Paris |
| Country | France |
