Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution (~250 nm), inside living biological cells is a challenging problem. State-of-the-art CV approaches based on detection, tracking, optical flow or deep learning perform poorly for this problem. We propose an integrative approach, built upon physics based simulations, nanoscopy algorithms, and shallow ...

Mitochondria are essential energy-providing organelles of particular importance in energy-demanding tissue such as the heart. The production of mitochondria-derived vesicles (MDVs) is a cellular mechanism by which cells ensure a healthy pool of mitochondria. These vesicles are small and fast-moving objects not easily captured by imaging. In this work, we have tested the ability of the optical ...

Segmenting subcellular structures in living cells from fluorescence microscope images is a ground truth (GT)-deficient problem. The microscopes’ three-dimensional blurring function, finite optical resolution due to light diffraction, finite pixel resolution and the complex morphological manifestations of the structures all contribute to GT-hardness. Unsupervised segmentation approaches are quite ...