Classification between normal and osteoporotic cancellous

Abstract

The study and monitoring of cancellous bone is particularly important for medical image analyses which are generally related to orthopedics field. In order to understand more about the cancellous bone, a micro-CT allows acquiring 3D images to visualize the complex architecture of the trabecular bone. This study furthermore presents a new development of classifier to help in the distinction between normal and osteoporotic trabecular bone from the analyses of the morphological parameters. Osteoporosis is a condition that affects especially older women and is characterized by decrease in bone mass with decreased density and enlargement of bone spaces producing porosity and fTagility. Osteoporosis is the most common type of metabolic bone disease generating morphological alterations of the bone structure. Therefore, an intensive and accurate study of bone architecture is required to individuate the origin of the disease and to estimate its evolution. More particularly, the present study relates to the methods and systems for 3D features classification using Bayesian decision rules. Classification method in this study is considered as an important approach or tool for recognizing the cancellous bone failure such Osteoporosis's condition. This classifier are tested and validated by using the morphological datasets of the trabecular bone structure taken from normal and osteoporotic trabecular bone samples. These studies in advance will provide some add up value as part of the function in the commercial high visualization and analysis software system for medical diagnosis.