title: Genetic algorithm and image processing for osteoporosis diagnosis.
abstract: Osteoporosis is considered as a major public health threat. It is characterized by a decrease in the density of bone, decreasing its strength and leading to an increased risk of fracture. In this work, the morphological, topological and mechanical characteristics of 2 populations of arthritic and osteoporotic trabecular bone samples are evaluated using artificial intelligence and recently developed skeletonization algorithms. Results show that genetic algorithms associated with image processing tools can precisely separate the 2 populations.
authors.affiliation: PRISME institute of the University of Orleans, France. rachid.jennane@univ-orleans.fr
authors.forename: R
authors.initials: R
authors.lastname: Jennane
authors.forename: A
authors.initials: A
authors.lastname: Almhdie-Imjabber
authors.forename: R
authors.initials: R
authors.lastname: Hambli
authors.forename: O N
authors.initials: ON
authors.lastname: Ucan
authors.forename: C L
authors.initials: CL
authors.lastname: Benhamou
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001842:Bone and Bones / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010003:Osteoarthritis / Q000175:diagnosis / Q000473:pathology; D010024:Osteoporosis / Q000175:diagnosis* / Q000473:pathology