A Comparative Analysis of Deep Convolutional Networks for Automated Diagnosis of Retinal Detachment in Dogs

Key Points

• To evaluate the effectiveness of ResNet50V2 in diagnosing retinal detachment in dogs using fundus photographs.
• Used ResNet50V2 for analysis of canine fundus images.
• Conducted a comparative analysis against other deep learning models.
• Evaluated performance for automated diagnosis of retinal detachment.
• ResNet50V2 showed strong potential in identifying retinal detachment.
• Suggests scalability for use in veterinary practices for screening.
• Further validation needed across different devices and settings.