Using Self Organising Maps to Visualise Age Related Changes in Lumbar Vertebrae and Intervertebral Discs.

A human spine is a complicated structure of bones, joints, ligaments and muscles which all undergo a process of change with age. This paper describes the use of artificial intelligence in visualization and better understanding of the progressive and degenerative changes in human lumbar spine. Visualizing this pattern of change will be helpful in finding the correlations among the spinal features and understanding of how a change in one feature affects others. The self-organizing map (SOM) is an efficient tool for visualization of multidimensional numerical data. It is capable of projecting high-dimensional data onto a regular, usually 2-dimensional grid of neurons. In this paper, SOM is used to visualize the pattern of change in lumbar spine features with the varying age. The paper gives an idea of how the information can be acquired from SOM representations and how the SOM can be best utilized in exploratory data visualization. Data from the lumbar spine MRIs of 61 patients (both male and female) were used in this study. The age of patients ranged from 2 to 93 years. Information for vertebral height, disc height and disc signal intensities were recorded from the MRI scans. SOM then transformed the larger feature space to a smaller one for getting a more meaningful relation between the spinal features. Complexity is reduced and the data set is represented in the form of 2D map which is easier to understand and provides visual description.