MRAnnotator: A Multi-Anatomy Deep Learning Model for MRI Segmentation

Purpose To develop a deep learning model for multi-anatomy and many-class segmentation of diverse anatomic structures on MRI imaging.
Materials and Methods In this retrospective study, two datasets were curated and annotated for model development and evaluation. An internal dataset of 1022 MRI sequences from various clinical sites within a health system and an external dataset of 264 MRI sequences from an independent imaging center were collected. In both datasets, 49 anatomic structures were annotated as the ground truth. The …

class clinical cs.cv dataset datasets deep learning development diverse eess.iv evaluation health imaging materials model development mri retrospective segmentation study