Binary imaging analysis for comprehensive quantitative histomorphometry of peripheral nerve

Daniel A. Hunter, Arash Moradzadeh, Elizabeth L. Whitlock, Michael J. Brenner, Terence M. Myckatyn, Cindy H. Wei, Thomas H.H. Tung, Susan E. Mackinnon

Research output: Contribution to journalArticlepeer-review

150 Scopus citations


Quantitative histomorphometry is the current gold standard for objective measurement of nerve architecture and its components. Many methods still in use rely heavily upon manual techniques that are prohibitively time consuming, predisposing to operator fatigue, sampling error, and overall limited reproducibility. More recently, investigators have attempted to combine the speed of automated morphometry with the accuracy of manual and semi-automated methods. Systematic refinements in binary imaging analysis techniques combined with an algorithmic approach allow for more exhaustive characterization of nerve parameters in the surgically relevant injury paradigms of regeneration following crush, transection, and nerve gap injuries. The binary imaging method introduced here uses multiple bitplanes to achieve reproducible, high throughput quantitative assessment of peripheral nerve. Number of myelinated axons, myelinated fiber diameter, myelin thickness, fiber distributions, myelinated fiber density, and neural debris can be quantitatively evaluated with stratification of raw data by nerve component. Results of this semi-automated method are validated by comparing values against those obtained with manual techniques. The use of this approach results in more rapid, accurate, and complete assessment of myelinated axons than manual techniques.

Original languageEnglish
Pages (from-to)116-124
Number of pages9
JournalJournal of Neuroscience Methods
Issue number1
StatePublished - Oct 15 2007


  • Binary imaging analysis
  • Histomorphometry
  • Peripheral nerve
  • Semi-automated nerve morphometry


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