The use of artificial neural networks to estimate the mechanical competence of trabecular bone

• Grant number: 16/20497-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2017
• End date: March 31, 2018
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Erica Regina Filletti Nascimento
• Grantee: Isabella Ferreira Occhipinti
• Host Institution: Instituto de Química (IQ). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil

Abstract

The mechanical powers parameter (PCM) of the trabecular structure is estimated from the volume fraction of trabecular bone, trabecular connectivity, obtained through the Euler-Poincare tortuosity and elasticity of the trabecular meshwork, using the principal component analysis. Through this method, the MCP can be individually estimated for different trabecular sites. In this project, we will continue to investigate the possibility of applying Artificial neural networks (ANN) as an alternative to estimate the MCP considering different bone sites, namely vertebra and radio, whose images of the samples were obtained by computed microtomography. (AU)