Generating corneal panoramic images from contact specular microscope images

TL;DR

This paper presents an automated framework to generate full corneal panoramic images from contact specular microscope videos, enabling better detection of guttae and corneal assessment.

Contribution

The study introduces a novel automated system combining panoramic compositing and deep learning for guttae detection from contact specular microscope videos.

Findings

Successfully synthesized images from 94 corneal videos

Effective guttae detection using U-Net model

System demonstrated potential for clinical corneal analysis

Abstract

The contact specular microscope has a wider angle of view than that of the non-contact specular microscope but still cannot capture an image of the entire cornea. To obtain such an image, it is necessary to prepare film on the parts of the image captured sequentially and combine them to create a complete image. This study proposes a framework to automatically generate an entire corneal image from videos captured using a contact specular microscope. Relatively focused images were extracted from the videos and panoramic compositing was performed. If an entire image can be generated, it is possible to detect guttae from the image and examine the extent of their presence. The system was implemented and the effectiveness of the proposed framework was examined. The system was implemented using custom-made composite software, Image Composite Software (ICS, K.I. Technology Co., Ltd., Japan, internal algorithms not disclosed), and a supervised learning model using U-Net was used for guttae detection. Several images were correctly synthesized when the constructed system was applied to 94 different corneal videos obtained from Fuchs endothelial corneal dystrophy (FECD) mouse model. The implementation and application of the method to the data in this study confirmed its effectiveness. Owing to the minimal quantitative evaluation performed, such as accuracy with implementation, it may pose some limitations for future investigations.