Our study introduces a label-free imaging and quantitative analysis approach for investigating lipofuscin aggregates in human brain tissue. Leveraging the colocalization of lipofuscin with cell soma, our novel method accurately identifies and counts cells, especially large neurons. Achieving an impressive 92% accuracy at submicron resolution, our label-free approach outperforms the commonly used Nissl stain. We develop a robust segmentation technique for lipofuscin aggregates, revealing layered structures in the cortical gray matter, potentially associated with cell distribution. Furthermore, we validate our results using state-of-the-art techniques, including fluorescence lifetime imaging microscope and sub-micron resolution two photon imaging. Our findings contribute valuable insights into neurodegenerative diseases and hold promise for future diagnostic advancements.
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