Optimization of cell annotation process: combining manual and automatic labeling in biomedical data analysis optoelectronic systems

Abstract

The advantages of the hybrid approach, common errors, and ways to minimize them are discussed. The results demonstrate that combined annotation enables faster preparation of training datasets without significant loss of quality, especially when working with large volumes of images. This approach may be beneficial for automated biomedical data analysis systems where rapid scaling is required without compromising accuracy.