Given a short query with keyphrases about a research idea in 2017 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: I want to learn to synthesize retinal images directly from data.

Keyphrases: image synthesis fundus images binary vessel tree

Dataset description:
MuseScore: The MuseScore dataset is a collection of 344,166 audio and MIDI pairs downloaded from MuseScore website. The audio is usually synthesized by the MuseScore synthesizer.
WebVision: The WebVision dataset is designed to facilitate the research on learning visual representation from noisy web data. It is a large scale web images dataset that contains more than 2.4 million of images crawled from the Flickr website and Google Images search.
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.
SNIPS: The SNIPS Natural Language Understanding benchmark is a dataset of over 16,000 crowdsourced queries distributed among 7 user intents of various complexity:   SearchCreativeWork (e.g. Find me the I, Robot television show), GetWeather (e.g.

Options:- A: MuseScore  B: WebVision  C: DRIVE  D: SNIPS
DRIVE