Automatic reconstruction of the muscle architecture from the superficial layer fibres data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932185" target="_blank" >RIV/49777513:23520/17:43932185 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.cmpb.2017.08.002" target="_blank" >http://dx.doi.org/10.1016/j.cmpb.2017.08.002</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cmpb.2017.08.002" target="_blank" >10.1016/j.cmpb.2017.08.002</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic reconstruction of the muscle architecture from the superficial layer fibres data

Popis výsledku v původním jazyce

Background and objective: Physiological cross-sectional area (PCSA) of a muscle plays a significant role in determining the force contribution of muscle fascicles to skeletal movement. This parameter is typically calculated from the lengths of muscle fibres selectively sampled from the superficial layer of the muscle. However, recent studies have found that the length of fibres in the superficial layer often differs significantly (p &lt; 0.5) from the length of fibres in the deep layer. As a result, PCSA estimation is inaccurate. In this paper, we propose a method to automatically reconstruct fibres in the whole volume of a muscle from those selectively sampled on the superficial layer. Methods: The method performs a centripetal Catmull–Rom interpolation of the input fibres within the volume of a muscle represented by its 3D surface model, automatically distributing the fibres among multiple heads of the muscle and shortening the deep fibres to support large attachment areas with extremely acute angles. Results: Our C++ implementation runs in a couple of seconds on commodity hardware providing realistic results for both artificial and real data sets we tested. Conclusions: The fibres produced by the method can be used directly to determine the personalised mechanical muscle functioning. Our implementation is publicly available for the researchers at https://mi.kiv.zcu.cz/.

Název v anglickém jazyce

Automatic reconstruction of the muscle architecture from the superficial layer fibres data

Popis výsledku anglicky

Background and objective: Physiological cross-sectional area (PCSA) of a muscle plays a significant role in determining the force contribution of muscle fascicles to skeletal movement. This parameter is typically calculated from the lengths of muscle fibres selectively sampled from the superficial layer of the muscle. However, recent studies have found that the length of fibres in the superficial layer often differs significantly (p &lt; 0.5) from the length of fibres in the deep layer. As a result, PCSA estimation is inaccurate. In this paper, we propose a method to automatically reconstruct fibres in the whole volume of a muscle from those selectively sampled on the superficial layer. Methods: The method performs a centripetal Catmull–Rom interpolation of the input fibres within the volume of a muscle represented by its 3D surface model, automatically distributing the fibres among multiple heads of the muscle and shortening the deep fibres to support large attachment areas with extremely acute angles. Results: Our C++ implementation runs in a couple of seconds on commodity hardware providing realistic results for both artificial and real data sets we tested. Conclusions: The fibres produced by the method can be used directly to determine the personalised mechanical muscle functioning. Our implementation is publicly available for the researchers at https://mi.kiv.zcu.cz/.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Computer Methods and Programs in Biomedicine

ISSN

0169-2607

e-ISSN

—

Svazek periodika

150

Číslo periodika v rámci svazku

October 2017

Stát vydavatele periodika

IE - Irsko

Počet stran výsledku

11

Strana od-do

85-95

Kód UT WoS článku

000410581900008

EID výsledku v databázi Scopus

2-s2.0-85027870150