FCN-based approach for the automatic segmentation of bone surfaces in ultrasound images

Purpose A new algorithm, based on fully convolutional networks (FCN), is proposed for the automatic localization of the bone interface in ultrasound (US) images. The aim of this paper is to compare and validate this method with (1) a manual segmentation and (2) a state-of-the-art method called confi...

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Veröffentlicht in:	International journal for computer assisted radiology and surgery Jg. 13; H. 11; S. 1707 - 1716
Hauptverfasser:	Villa, M., Dardenne, G., Nasan, M., Letissier, H., Hamitouche, C., Stindel, E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.11.2018 Springer Nature B.V
Schlagworte:	Algorithms Annotations Artificial neural networks Bone and Bones - diagnostic imaging Computer Imaging Computer Science Health Informatics Humans Image Processing, Computer-Assisted - methods Image segmentation Imaging Medicine Medicine & Public Health Observer Variation Original Article Pattern Recognition and Graphics Radiology Recall Reproducibility of Results Root-mean-square errors Sensitivity and Specificity Surgery Ultrasonic imaging Ultrasonography - methods Vision Fully conventional network Computer-assisted orthopedic surgery Bone Segmentation Ultrasound
ISSN:	1861-6410, 1861-6429, 1861-6429
Online-Zugang:	Volltext
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