Given a short query with keyphrases about a research idea in 2019 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 new two-stage method for 3D plane segmentation from single-image.

Keyphrases: 3d plane segmentation images

Dataset description:
NuCLS: The NuCLS dataset contains over 220,000 labeled nuclei from breast cancer images from TCGA. These nuclei were annotated through the collaborative effort of pathologists, pathology residents, and medical students using the Digital Slide Archive.
Unite the People: Unite The People is a dataset for 3D body estimation. The images come from the Leeds Sports Pose dataset and its extended version, as well as the single person tagged people from the MPII Human Pose Dataset.
Brain US: This brain anatomy segmentation dataset has 1300 2D US scans for training and 329 for testing. A total of 1629 in vivo B-mode US images were obtained from 20 different subjects (age<1 years old) who were treated between 2010 and 2016.
ScanNet: ScanNet is an instance-level indoor RGB-D dataset that includes both 2D and 3D data. It is a collection of labeled voxels rather than points or objects.

Options:- A: NuCLS  B: Unite the People  C: Brain US  D: ScanNet
ScanNet