Experts has a new look! Let us know what you think of the updates.

Provide feedback
Home
Scholarly Works
Annotation burden reduction in deep learning for...
Conference

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.

Authors

Hong T; Fang Q

Publication Date

January 1, 2023

DOI

10.1364/NTM.2023.JTu4B.12

Conference proceedings

Novel Techniques in Microscopy NTM 2023