Abstract
It is known that the cross section of human femoral bones can provide a link between bone structure and age, and information about possible bone diseases. Traditional approaches to bone cross section analysis is primarily carried out manually, which are slow and prone to human errors. In this paper we present a new method using digital image processing techniques for quantitative analysis of femoral bones. We demonstrate that such a system is able to extract various bone features consistently and provides more reliable statistics for the bones. As a consequence, we will be able to automatically correlate bone features with age and possibly with age related bone deceases such as osteoporosis. This provides a basis enabling us to develop knowledge-based computer vision systems for automated bone image analysis.
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