Deep-learning-based Segmentation of Fundus Photographs to Detect Central Serous Chorioretinopathy

We asked three ophthalmologists including two licensed ophthalmologists (grader 1 & 2) and one ophthalmology resident (grader 3) to segment the entire SRF area in the retinal images. First, we prepared the dataset in Google Drive. Second, the users can upload the code file in Google Drive and open the file on the Google Drive page on the web browser.

Third, prepare the dataset in Google Drive and match the folder location of the code with the address of the actual folders. In our experiment as an example, we saved the training dataset at "csc/segmentation/train/" and the test dataset at "csc/segmentation/test/" in our own Google Drive. Fourth, click the play button to the left of the code cell one by one.

The second code cell links the datasets to this Colaboratory notebook using Google Drive. The manuscript of the study was accepted to TVST, ARVO journal.