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Semiautomatic extraction of cortical thickness and diaphyseal curvature from CT scans.
Dupej, Ján; Lacoste Jeanson, Alizé; Pelikán, Josef; Bruzek, Jaroslav.
Afiliação
  • Dupej J; Department of Anthropology and Human Genetics, Faculty of Sciences, Charles University, Vinicná 7, Praha 2, 128 43, Czech Republic.
  • Lacoste Jeanson A; Department of Software and Computer Science Education, Charles University, Faculty of Mathematics and Physics, Malostranské Námestí 25, Praha 1, 118 00, Czech Republic.
  • Pelikán J; Department of Anthropology and Human Genetics, Faculty of Sciences, Charles University, Vinicná 7, Praha 2, 128 43, Czech Republic.
  • Bruzek J; Department of Software and Computer Science Education, Charles University, Faculty of Mathematics and Physics, Malostranské Námestí 25, Praha 1, 118 00, Czech Republic.
Am J Phys Anthropol ; 164(4): 868-876, 2017 12.
Article em En | MEDLINE | ID: mdl-28913906
ABSTRACT
The understanding of locomotor patterns, activity schemes, and biological variations has been enhanced by the study of the geometrical properties and cortical bone thickness of the long bones measured using CT scan cross-sections. With the development of scanning procedures, the internal architecture of the long bones can be explored along the entire diaphysis. Recently, several methods that map cortical thickness along the whole femoral diaphysis have been developed. Precise homology is vital for statistical examination of the data; however, the repeatability of these methods is unknown and some do not account for the curvature of the bones. We have designed a semiautomatic workflow that improves the morphometric analysis of cortical thickness, including robust data acquisition with minimal user interaction and considering the bone curvature. The proposed algorithm also performs automatic landmark refinement and rigid registration on the extracted morphometric maps of the cortical thickness. Because our algorithm automatically reslices the diaphysis into 100 cross-sections along the medial axis and uses an adaptive thresholding method, it is usable on CT scans that contain soft tissues as well as on bones that have not been oriented specifically prior to scanning. Our approach exhibits considerable robustness to error in user-supplied landmarks, suppresses distortion caused by the curvature of the bones, and calculates the curvature of the medial axis.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Tomografia Computadorizada por Raios X / Fêmur Limite: Female / Humans / Male Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Tomografia Computadorizada por Raios X / Fêmur Limite: Female / Humans / Male Idioma: En Ano de publicação: 2017 Tipo de documento: Article