Maryam Sadat Mahmoodi

Accurate tracking of lytic granules via simultaneous particle tracking, phase retrieval and point spread function reconstruction

This paper develops a framework for simultaneous particle tracking, phase retrieval, and PSF reconstruction to improve 3D tracking of lytic granules in T cells.

SPTnet: a deep learning framework for end-to-end single-particle tracking and motion dynamics analysis

SPTnet is a deep learning framework that improves single-particle tracking by directly inferring trajectories and motion parameters from microscopy videos, outperforming traditional methods in challenging conditions.