Hong Yan

EmbSAM provides a framework for 3D cell membrane segmentation in C. elegans embryos using deep learning and the Segment Anything Model, enabling analysis of cell shape dynamics during development.

The paper quantifies cell morphology in C. elegans embryos, revealing that signaling pathways regulate both cell fate asymmetry and volume asymmetry.

The paper develops CShaper, a deep-learning-based pipeline to generate a 4D morphological atlas of C. elegans embryos, characterizing cell shape, migration, and cell-cell contacts across development.

WBC-Profiler automatically extracts complex signatures from microscopic images to construct leukocyte profiles without human intervention.