Semiautomatic extraction of cortical thickness and diaphyseal curvature from CT scans

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F17%3A10367102" target="_blank" >RIV/00216208:11310/17:10367102 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/17:10367102

Výsledek na webu

<a href="http://dx.doi.org/10.1002/ajpa.23315" target="_blank" >http://dx.doi.org/10.1002/ajpa.23315</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/ajpa.23315" target="_blank" >10.1002/ajpa.23315</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Semiautomatic extraction of cortical thickness and diaphyseal curvature from CT scans

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Semiautomatic extraction of cortical thickness and diaphyseal curvature from CT scans

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10600 - Biological sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

American Journal of Physical Anthropology

ISSN

0002-9483

e-ISSN

—

Svazek periodika

164

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

868-876

Kód UT WoS článku

000415905800016

EID výsledku v databázi Scopus

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