Validation of parametric mesh generation for subject-specific cerebroarterial trees using modified Hausdorff distance metrics

Accurate subject-specific vascular network reconstruction is a critical task for the hemodynamic analysis of cerebroarterial circulation. Vascular skeletonization and computational mesh generation for large sections of cerebrovascular trees from magnetic resonance angiography (MRA) is an error-prone...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Computers in biology and medicine Jg. 100; S. 209 - 220
Hauptverfasser:	Ghaffari, Mahsa, Sanchez, Lea, Xu, Guoren, Alaraj, Ali, Zhou, Xiaohong Joe, Charbel, Fady T., Linninger, Andreas A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.09.2018 Elsevier Limited
Schlagworte:	Angiography Arteries Bifurcations Blood vessels Cerebral arterial tree Cerebral Arteries - diagnostic imaging Cerebral Arteries - physiopathology Cerebral blood flow Cerebrovascular Circulation Cerebrovascular system Computational grids Computer applications Computer Simulation Confidence Correlation analysis Data banks Finite element method Hausdorff distance Hemodynamics Human subjects Humans Image processing Image reconstruction Image segmentation Magnetic fields Magnetic resonance Magnetic Resonance Angiography Mathematical models Mesh generation Mesh validation Model accuracy Models, Cardiovascular Morphological analysis Morphology Parametric structured mesh Pointwise surface distance Shape similarity index Similarity measures Statistical analysis Time dependence Trees Pointwise surface distance Shape similarity index Morphological analysis Mesh validation Hausdorff distance Cerebral arterial tree Parametric structured mesh
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!