Self-supervised learning framework application for medical image analysis: a review and summary
Abstract Manual annotation of medical image datasets is labor-intensive and prone to biases.Moreover, the rate at which image data accumulates significantly outpaces the speed of manual annotation, posing a challenge to the advancement of machine learning, particularly in the realm of supervised learning.Self-supervised learning is an emerging fiel