BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models. (arXiv:2112.03916v2 [eess.IV] UPDATED)

Deep learning has brought the most profound contribution towards biomedical
image segmentation to automate the process of delineation in medical imaging.
To accomplish such task, the models are required to be trained using huge
amount of annotated or labelled data that highlights the region of interest
with a binary mask. However, efficient generation of the annotations for such
huge data requires expert biomedical analysts and extensive manual effort. It
is a tedious and expensive task, while also being vulnerable to …

arxiv bt framework learning segmentation self-supervised learning supervised learning