Reliable and reproducible classification system for scoliotic radiograph using image processing techniques.

Abstract

Scoliosis classification is useful for guiding the treatment and testing the clinical outcome. State-of-the-art classification procedures are inherently unreliable and non-reproducible due to technical and human judgmental error. In the current diagnostic system each examiner will have diagrammatic summary of classification procedure, number of scoliosis curves, apex level, etc. It is very difficult to define the required anatomical parameters in the noisy radiographs. The classification system demands automatic image understanding system. The proposed automated classification procedures extracts the anatomical features using image processing and applies classification procedures based on computer assisted algorithms. The reliability and reproducibility of the proposed computerized image understanding system are compared with manual and computer assisted system using Kappa values.