In organelle imaging, segmentation aims to accurately delineate pixels or voxels corresponding to target organelles from background, noise, and other cellular structures in microscopy images, thereby generating masks suitable for quantitative analysis. Robust segmentation is foundational to downstream quantification, including morphological characterization, spatial distribution analysis, temporal trajectory tracking, and the detection of key biological events.
Although super-resolution techniques widely used in live-cell imaging substantially improve spatial resolution, they also introduce challenges such as signal-to-noise variability, phototoxicity constraints, and increased imaging artifacts. Consequently, developing segmentation algorithms that maintain…