Genetic algorithm and image processing for osteoporosis diagnosis

Author

Jennane, R. ; Almhdie-Imjabber, A. ; Hambli, R. ; Ucan, O.N. ; Benhamou, C.L.

Author_Institution

PRISME Inst., Univ. of Orleans, Orleans, France

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

5597

Lastpage

5600

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.

Keywords

artificial intelligence; biomechanics; bone; diseases; fracture; genetic algorithms; medical image processing; patient diagnosis; arthritic bone samples; artificial intelligence; bone density reduction; bone strength; fracture risk; genetic algorithm; medical image processing; osteoporosis; osteoporotic trabecular bone samples; patient diagnosis; skeletonization algorithms; Bones; Classification algorithms; Feature extraction; Finite element methods; Media; Support vector machines; Algorithms; Artificial Intelligence; Bone and Bones; Humans; Image Interpretation, Computer-Assisted; Osteoarthritis; Osteoporosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5626804

Filename

5626804