GOALS will be organized in conjunction with the 9th MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA), a Full-day Satellite Event of the MICCAI 2022 conference in Singapore.

GOALS will release 300 circumpapillary OCT images collected by two different devices. This dataset can not only supports research on the application of deep learning methods in OCT image analysis, but also on the adaptive multi-domain algorithms. Optical Coherence Tomography (OCT) is a powerful tool for the diagnosis of ocular diseases, since the image acquisition consists of a contactless, non-invasive method that gives a set of images of the main retinal structures in real-time. Compared with color fundus images, which can only provide retinal surface information, OCT images can provide cross-sectional information of the retina, so it can be a more accurate analysis of the retinal structure. Segmentation and quantification of layer thickness are useful in the diagnosis of many retinal and optic nerve disorders, for example, glaucoma, macular degeneration, or diabetic retinopathy. In the diagnosis of glaucoma, it is easier to detect early cases using OCT than using fundus color images.

GOALS challenge consists of TWO Tasks:

        1. a segmentation task to determine the retinal nerve fiber layer, ganglion cell-inner plexiform layer, and choroidal layer, which are helpful for diagnosis and differentiation of glaucoma;

        2. an automatic diagnosis task of glaucoma.

Please visit the URL of the challenge: https://aistudio.baidu.com/aistudio/competition/detail/230 (CLOSED NOW)

Now, to access the details of the data and evaluation framework, please visit the following URL and join the CHALLENGE: