Replication Data for: Automated Cone Photoreceptors Detection in Adaptive Optics Flood-Illumination Ophthalmoscopy

The dataset is made available and consists of two partitions, a training and a testing dataset. The training dataset contains 625 annotated patches (from 20 images from 18 subjects) and the testing dataset contains 54 annotated patches (from 18 images from 18 subjects). The testing dataset contains annotations from four different graders. Further information about the annotations can be found in paper. Training: The training image patches are individual .tiff files with the dimension of (128x128 pixels). Use any tiff-reader you want. Test: The test image patches and annotations are .tiff files with the dimensions of (3x128x128). NOTE: Need to be loaded using imageio.mimread() Link to code: https://gitlab.com/radiology/eye/ao-vision/ao-fio-conedetect Python to load the image files. import imageio import tifffile # Training-dataset images image_training_path = "path/to/data/image.tiff" image_array = tifffile.imread(image_training_path) # Test-dataset images image_test_path = "path/to/data/image.tiff" image_array = imageio.mimread(image_test_path) # Not using mimread will lead to wrong loading of the tiff-file