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BY 4.0 license Open Access Published by De Gruyter September 18, 2019

Automated alignment detection of an additively manufactured Z-frame marker to process instrument targeting signals in interventional MRI

  • Robert Odenbach EMAIL logo , Parisa Parsanejad and Michael Friebe

Abstract

MRI-guided interventions (iMRI, e.g. prostate biopsy) are usually performed under a free-hand instrument targeting approach to guide and feed the instrument (e.g. biopsy needle) along the desired trajectory. However, this technique requires many iterative movements either from the interventionist or of the patient (with the MRI table) in and out of the MRI tunnel, which is cumbersome, time-consuming and expensive. To overcome these downsides, interventional MRI procedures can be facilitated with remotely controllable assistance systems for instrument alignment. Such systems require an accurate registration and tracking of the position and orientation of the instrument. Passive fiducial marker frames (e.g. additively manufactured Z-frame marker) are capable of providing full information about a device´s orientation within the image. In this paper, we present an automated alignment detection algorithm to track a Z-marker from system-independent screen-captured images. We evaluated the precision of the detection algorithm by analysing its computation results from schematic gold standard images in different marker orientations in comparison to MR-images with the same orientations. Our combined setup consists of a precise alignment system, an additively manufactured Z-frame marker and the related detection algorithm. It offers a fast, simple, independent and accurate automated instrument targeting for iMRI. For future work, we plan to conduct phantom targeting tests in combination with robotic alignment systems.

Published Online: 2019-09-18
Published in Print: 2019-09-01

© 2019 by Walter de Gruyter Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Downloaded on 26.2.2024 from https://www.degruyter.com/document/doi/10.1515/cdbme-2019-1570538316/html
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