Computational spatial analysis of peripheral nervous system anatomical data

The quantitative analysis of spatial patterns and mathematical modeling of the organization of biological structure on the basis of microscopy images remain in the center of attention of the PNS and CNS communities. My research focuses on development of a systematic approach to spatial analysis in PNS imaging with a specific focus on three aspects:

  • Quantitative descriptions of continuous spatial variation and associated spatial autocorrelation, cooccurence and colocalization (in collaboration with Terry Powley group)
  • Point-pattern analysis and quantitative description of relation/correlation between spatially arranged classes of structures (collaboration with Leif Havton group and Warren Grill group)
  • Spatial analysis of network-like structures and modeling the organization and architecture of the enteric nervous system (collaboration with Marthe Howard group and Bob Heuckeroth lab, computational work with Alex Pothen).
  • Automated segmentation of unmyelinated fibers, and other hard-to-segment structures in PNA (collaboration with Terry Powley, Leif Havton, and Murat Dundar)

This research is generously supported by the NIH SPARC initiative.

Page updated on 2022-01-17 12:51:24 -0500