Morphometric analysis of neurons from the marginal and substantia gelatinosa layers of human spinal cord: Classification according to laminar organization

The main goal of morphometric analysis of neuronal images, except for getting information about their geometry and dendritic branching patterns, is their classification based on laminar organization. The majority of contemporary techniques for image analysis are based on the application of fractal theory, which has some limitations on results analysis. For that reasons, the new, mostly nonfractal techniques for image analysis had been designed in the past few years. This study shows the analysis of morphometry of the human spinal cord neurons from the marginal (lamina I) and substantia gelatinosa (laminae I-II). For the analysis of neuron images two techniques of morphometric analysis were used: box-counting method as a mainly used technique for fractal analysis, and circle-counting method as a newly designed technique for measuring the length of dendrites. The use of these methods for neurons of the mentioned regions of human spinal cord showed that circlecounting method had given more accurate results than fractal analysis method. When the proposed method was used for the analysis of neuronal images, it was possible to classify neurons according to their laminar position