Estimation of muscle fascicle orientation in ultrasonic images

We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.

Metadaten
Verfasserangaben:	Regina Pohle-Fröhlich, Christoph Dalitz, Charlotte Richter ORCiD, Tobias Hahnen, Benjamin Stäudle ORCiD, Kirsten Albracht ORCiD
DOI:	https://doi.org/10.5220/0008933900790086
ISBN:	978-989-758-402-2
Titel des übergeordneten Werkes (Englisch):	Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5
Verlag:	SciTePress
Verlagsort:	Setúbal, Portugal
Dokumentart:	Konferenzveröffentlichung
Sprache:	Englisch
Erscheinungsjahr:	2020
Datum der Publikation (Server):	15.05.2020
Erste Seite:	79
Letzte Seite:	86
Bemerkung:	15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISAPP 2020, Valletta, Malta
Link:	https://doi.org/10.5220/0008933900790086
Zugriffsart:	weltweit
Fachbereiche und Einrichtungen:	FH Aachen / Fachbereich Medizintechnik und Technomathematik
	FH Aachen / IfB - Institut für Bioengineering
open_access (DINI-Set):	open_access
Lizenz (Deutsch):	Creative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung

Open Access