title: Genetic algorithm-neural network estimation of cobb angle from torso asymmetry in scoliosis.
abstract: 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 degrees in two-thirds, and within 10 degrees 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.
authors.affiliation: Dept. of Surgery, Faculty of Medicine, University of Calgary, AB, Canada. jljaremk@ucalgary.ca
authors.forename: Jacob L
authors.initials: JL
authors.lastname: Jaremko
authors.forename: Philippe
authors.initials: P
authors.lastname: Poncet
authors.forename: Janet
authors.initials: J
authors.lastname: Ronsky
authors.forename: James
authors.initials: J
authors.lastname: Harder
authors.forename: Jean
authors.initials: J
authors.lastname: Dansereau
authors.forename: Hubert
authors.initials: H
authors.lastname: Labelle
authors.forename: Ronald F
authors.initials: RF
authors.lastname: Zernicke
mesh_terms: D000005:Abdomen / Q000033:anatomy & histology; D000293:Adolescent; D000328:Adult; D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods; D001415:Back / Q000033:anatomy & histology; D002648:Child; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D011859:Radiography; D015203:Reproducibility of Results; D012600:Scoliosis / Q000175:diagnosis* / Q000000981:diagnostic imaging; D013909:Thorax / Q000033:anatomy & histology