Annotation burden reduction in deep learning for lensless imaging flow cytometry with a self-supervised pretext task
Abstract
A self-supervised pretext task is developed based on flow profile and motion extraction for cell detection in a lensless imaging flow cytometer. It reduces the annotation burden, automatically selects usable frames, and improves detection performance.