title: Bone image segmentation.
abstract: Characteristics of microscopic structures in bone cross sections carry essential clues in age determination in forensic science and in the study of age-related bone developments and bone diseases. Analysis of bone cross sections represents a major area of research in bone biology. However, traditional approaches in bone biology have relied primarily on manual processes with very limited number of bone samples. As a consequence, it is difficult to reach reliable and consistent conclusions. In this paper we present an image processing system that uses microstructural and relational knowledge present in the bone cross section for bone image segmentation. This system automates the bone image analysis process and is able to produce reliable results based on quantitative measurements from a large number of bone images. As a result, using large databases of bone images to study the correlation between bone structural features and age-related bone developments becomes feasible.
authors.affiliation: Department of Computer Science, University of Melbourne, Parkville, Victoria, Australia.
authors.forename: Z Q
authors.initials: ZQ
authors.lastname: Liu
authors.forename: H L
authors.initials: HL
authors.lastname: Liew
authors.forename: J G
authors.initials: JG
authors.lastname: Clement
authors.forename: C D
authors.initials: CD
authors.lastname: Thomas
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001842:Bone and Bones / Q000166:cytology* / Q000000981:diagnostic imaging; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D005269:Femur / Q000166:cytology / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008852:Microradiography; D018715:Microscopy, Video; D008875:Middle Aged