Needle Segmentation in 3D Ultrasound Volumes Based on Machine Learning for Needle Steering
Résumé
To achieve needle steering and guide a flexible needle,
it is necessary to localize it first. In the case of 3D
ultrasound (US) in B-mode, the poor imaging quality and
artefacts make it difficult to determine the needle pose.
Needle localization issues specific to needle steering are
reviewed in [1]. In [2], we proposed an observer of the
needle tip pose. In [3], we detailed a machine learning
approach for needle localization in 3D US volumes. In
this paper, we describe the interconnection of both
methods for precise curved needle localization in the
context of needle steering.
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