Abstract:
:In this paper, we propose an automated method to reconstruct the three-dimensional (3-D) needle shape during needle insertion procedures using only 2-D transverse ultrasound (US) images. Using a set of transverse US images, image processing and random sample consensus are used to locate the needle within each image and estimate the needle shape. The method is validated with an in vitro needle insertion setup and a transparent tissue phantom, where two orthogonal cameras are used to capture the true 3-D needle shape for verification. Results showed that the use of at least three images obtained at 75% of the maximum insertion depth or greater allows for maximum needle shape estimation errors of less than 2 mm. In addition, the needle shape can be calculated consistently as long as the needle can be identified in 30% of the transverse US images obtained. Application to permanent prostate brachytherapy is also presented, where the estimated needle shape is compared to manual segmentation and sagittal US images. Our method is intended to help to assess needle placement during manual or robot-assisted needle insertion procedures after the needle has been inserted.
journal_name
IEEE J Biomed Health Informjournal_title
IEEE journal of biomedical and health informaticsauthors
Waine M,Rossa C,Sloboda R,Usmani N,Tavakoli Mdoi
10.1109/JBHI.2015.2477829subject
Has Abstractpub_date
2016-11-01 00:00:00pages
1621-1631issue
6eissn
2168-2194issn
2168-2208journal_volume
20pub_type
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