Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation

Understand

We tackle biomedical image segmentation in the scenario of only a few labeled brain MR images.

• This is an important and challenging task in medical applications, where manual annotations are time-consuming.
• Current multi-atlas based segmentation methods use image registration to warp segments from labeled images onto a new scan.
• In a different paradigm, supervised learning-based segmentation strategies have gained popularity.