Fibrous Dysplasia Characterization Using Lacunarity Analysis.

Fibrous dysplasia (FD) is a developmental anomaly in which the normal medullary space of the affected bone is replaced by fibro-osseous tissue. This condition is typically encountered in adolescents and young adults. It affects the maxillofacial region and it can often cause severe deformity and asy...

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Publicado en:Journal of Digital Imaging Vol. 29; no. 1; pp. 134 - 141
Autores principales: Cordeiro, Mirna, Backes, André, Júnior, Antônio, Gonçalves, Elmar, de Oliveira, Jefferson
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Feb2016
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
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        atl: Fibrous Dysplasia Characterization Using Lacunarity Analysis.
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          Cordeiro, Mirna
          Backes, André
          Júnior, Antônio
          Gonçalves, Elmar
          de Oliveira, Jefferson
        affil: School of Dentistry, University of São Paulo, Av. Professor Lineu Prestes 2227-05508-000 São Paulo Brazil
      sug:
        subj:
          Fibrous Dysplasia of Bone Diagnosis
          Fibrous Dysplasia of Bone Radiography
          Tomography, Spiral Computed
          Radiographic Image Interpretation, Computer-Assisted
          Radiographic Image Enhancement
          Decision Trees
          Descriptive Research
          Exploratory Research
          Human
      ab: Fibrous dysplasia (FD) is a developmental anomaly in which the normal medullary space of the affected bone is replaced by fibro-osseous tissue. This condition is typically encountered in adolescents and young adults. It affects the maxillofacial region and it can often cause severe deformity and asymmetry. Therefore, accurate diagnosis is critical to determine the appropriate treatment of each case. In this sense, computed tomography (CT) is a relevant resource among the imaging techniques for correct diagnosis of this condition. Thus, in this paper, we propose to analyze fibrous dysplasia through its texture pattern. To accomplish this task, we propose to use lacunarity analysis, a multiscale method for describing patterns of spatial dispersion. Results indicated lower lacunarity values for fibrous dysplasia in comparison to normal bone samples, an indication that their texture images are more homogeneous, and a high separability between the classes when using principal component analysis (PCA) and decision trees for statistical analysis.
      pubtype: Academic Journal
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        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
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    language: English
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