Genetic Algorithm–Neural Network Estimation of Cobb Angle from Torso Asymmetry in Scoliosis

Scoliosis severity, measured by the Cobb angle, was estimated by artificial neural network from indices of torso surface asymmetry using a genetic algorithm to select the optimal set of input torso indices. Estimates of the Cobb angle were accurate within 5° in two-thirds, and within 10° in six-sevenths, of a test set of 115 scans of 48 scoliosis patients, showing promise for future longitudinal studies to detect scoliosis progression without use of X-rays.