On the possibility of objective identification of human vertebrae through pattern recognition algorithms

The task of finding whether vertebral levels of the human spine can be mathematically differentiated is posed, using a morphometric database of the vertebral quantitative morphology as a training set. There is no certainty in the medical community about this possibility. The axial projections of a number of vertebrae were digitized and their features quantified by automatic image analysis algorithms. These measurements build a spinal morphometric database. After the application of feature selection procedures, the selected measurements are used as inputs to different pattern recognition algorithms try to find whether vertebral levels can be distinguished. The authors have proved the capability to fulfil this classification with a small degree of uncertainty. Artificial neural networks, in particular, have shown their capability to perform well in this difficult pattern recognition task