Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: A system for A/V classification in retinal images.

Keyphrases: a/v classification retinal images

Dataset description:
ORVS: The ORVS dataset has been newly established as a collaboration between the computer science and visual-science departments at the University of Calgary. This dataset contains 49 images (42 training and seven testing images) collected from a clinic in Calgary-Canada.
ADAM: ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA. The ADAM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Age-related Macular degeneration (AMD) and segmentation of lesions in fundus photos from AMD patients.
DRIVE: The Digital Retinal Images for Vessel Extraction (DRIVE) dataset is a dataset for retinal vessel segmentation. It consists of a total of JPEG 40 color fundus images; including 7 abnormal pathology cases.
HRF: The HRF dataset is a dataset for retinal vessel segmentation which comprises 45 images and is organized as 15 subsets. Each subset contains one healthy fundus image, one image of patient with diabetic retinopathy and one glaucoma image.

Options:- A: ORVS  B: ADAM  C: DRIVE  D: HRF
DRIVE