Shifting To Machine Supervision: Annotation-efficient Semi And Self-supervised Learning For Automatic Medical Image Segmentation And Classification

The S4MI pipeline utilizes self-supervised and semi-supervised learning techniques to improve medical imaging analysis, reducing the need for costly and time-consuming annotation. Results show superior performance in classification and segmentation tasks, with the code being openly accessible for further development.