Algorithmic Quantification of Skull Bone Density

Abstract

It is estimated that over 200 million people worldwide experience a decrease in bone strength associated with osteoporosis. This causes increased susceptibility to fracture which represents one of the critical challenges of aging population. Therefore, novel approaches in assessing overall bone integrity are introduced. These approaches included the use of micro CT scan of skull bone images of mouse which allow to study a new mouse model with gap junction protein mutation, and compare normal and diseased animals. We propose skull bone detection algorithm capable of successfully detecting skull bone density. The proposed method has two functions: visual and numerical. Visual function is expressed through detection and indication of the potential bone tissue by marking it in a different color and distinguishing it from the background. Numerical function enables quantification of the amount of detected skull bone by calculating its numerical content equivalent.