Artificial intelligence-based software for digital assessment of reparative bone tissue regeneration
Abstract
Objective. To develop artificial intelligence-based software algorithm for quantitative assessment of reparative bone tissue regeneration, as well as to compare the results of histomorphometric analysis carried out by neural network and human. Material and methods. Morphometric parameters were determined and standardized. The authors developed artificial intelligence-based software algorithm with subsequent neural network training based on high-resolution images. Efficacy of human and software algorithm was compared. Results. Original software allows for automatic analysis of bone regenerate tissue composition within the shortest possible time. Conclusion. Original software may be equivalent for quick and effective analysis of bone regenerate tissue components. These data may be comparable with manual marking regarding reproducibility and accuracy.