Biomaterial Database

Capturing data from three-dimensional surfaces using fuzzy landmarks. 1998

C J Valeri, and T M Cole, and S Lele, and J T Richtsmeier

Department of Cell Biology and Anatomy, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.

Anatomical landmarks are defined as biologically meaningful loci that can be unambiguously defined and repeatedly located with a high degree of accuracy and precision. The neurocranial surface is characteristically void of such loci. We define a new class of landmarks, termed fuzzy landmarks, that will allow us to represent the form of the neurocranium. A fuzzy landmark represents the position of a biological structure that is precisely delineated, but occupies an area that is larger than a single point in the observer's reference system. In this study, we present a test case in which the cranial bosses are evaluated as fuzzy landmarks. Five fuzzy landmarks (the cranial bosses) and three traditional landmarks were placed repeatedly by a single observer on three-dimensional (3D) computed tomography (CT) surface reconstructions of pediatric dry skulls and skulls of pediatric patients, and directly on four of the same dry skulls using a 3Space digitizer. Thirty landmark digitizing trials from CT scans show an average error of 1.15 mm local to each fuzzy landmark, while the average error for the last ten trials was 0.75 mm, suggesting a learning curve. Data collected with the 3Space digitizer was comparable. Measurement error of fuzzy landmarks is larger than that of traditional landmarks, but is acceptable, especially since fuzzy landmarks allow inclusion of areas that would otherwise go unsampled. The information obtained is valuable in growth studies, clinical evaluation, and volume measurements. Our method of fuzzy landmarking is not limited to cranial bosses, and can be applied to any other anatomical features with fuzzy boundaries.

UI	MeSH Term	Description	Entries
D007091	Image Processing, Computer-Assisted	A technique of inputting two-dimensional or three-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer.	Biomedical Image Processing,Computer-Assisted Image Processing,Digital Image Processing,Image Analysis, Computer-Assisted,Image Reconstruction,Medical Image Processing,Analysis, Computer-Assisted Image,Computer-Assisted Image Analysis,Computer Assisted Image Analysis,Computer Assisted Image Processing,Computer-Assisted Image Analyses,Image Analyses, Computer-Assisted,Image Analysis, Computer Assisted,Image Processing, Biomedical,Image Processing, Computer Assisted,Image Processing, Digital,Image Processing, Medical,Image Processings, Medical,Image Reconstructions,Medical Image Processings,Processing, Biomedical Image,Processing, Digital Image,Processing, Medical Image,Processings, Digital Image,Processings, Medical Image,Reconstruction, Image,Reconstructions, Image
D007223	Infant	A child between 1 and 23 months of age.	Infants
D008953	Models, Anatomic	Three-dimensional representation to show anatomic structures. Models may be used in place of intact animals or organisms for teaching, practice, and study.	Anatomic Models,Models, Surgical,Moulages,Models, Anatomical,Anatomic Model,Anatomical Model,Anatomical Models,Model, Anatomic,Model, Anatomical,Model, Surgical,Moulage,Surgical Model,Surgical Models
D002648	Child	A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL.	Children
D003198	Computer Simulation	Computer-based representation of physical systems and phenomena such as chemical processes.	Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012886	Skull	The SKELETON of the HEAD including the FACIAL BONES and the bones enclosing the BRAIN.	Calvaria,Cranium,Calvarium,Skulls
D014057	Tomography, X-Ray Computed	Tomography using x-ray transmission and a computer algorithm to reconstruct the image.	CAT Scan, X-Ray,CT Scan, X-Ray,Cine-CT,Computerized Tomography, X-Ray,Electron Beam Computed Tomography,Tomodensitometry,Tomography, Transmission Computed,X-Ray Tomography, Computed,CAT Scan, X Ray,CT X Ray,Computed Tomography, X-Ray,Computed X Ray Tomography,Computerized Tomography, X Ray,Electron Beam Tomography,Tomography, X Ray Computed,Tomography, X-Ray Computer Assisted,Tomography, X-Ray Computerized,Tomography, X-Ray Computerized Axial,Tomography, Xray Computed,X Ray Computerized Tomography,X Ray Tomography, Computed,X-Ray Computer Assisted Tomography,X-Ray Computerized Axial Tomography,Beam Tomography, Electron,CAT Scans, X-Ray,CT Scan, X Ray,CT Scans, X-Ray,CT X Rays,Cine CT,Computed Tomography, Transmission,Computed Tomography, X Ray,Computed Tomography, Xray,Computed X-Ray Tomography,Scan, X-Ray CAT,Scan, X-Ray CT,Scans, X-Ray CAT,Scans, X-Ray CT,Tomographies, Computed X-Ray,Tomography, Computed X-Ray,Tomography, Electron Beam,Tomography, X Ray Computer Assisted,Tomography, X Ray Computerized,Tomography, X Ray Computerized Axial,Transmission Computed Tomography,X Ray Computer Assisted Tomography,X Ray Computerized Axial Tomography,X Ray, CT,X Rays, CT,X-Ray CAT Scan,X-Ray CAT Scans,X-Ray CT Scan,X-Ray CT Scans,X-Ray Computed Tomography,X-Ray Computerized Tomography,Xray Computed Tomography
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model