Please use this identifier to cite or link to this item: https://knowledgecommons.lakeheadu.ca/handle/2453/4527
Title: A mechanism for simplified scanner control with application to MRI-guided interventions
Authors: MacDonald, Matthew A.
Keywords: Magnetic Resonance Image (MRI)-guided interventions
Issue Date: 2016
Abstract: Magnetic Resonance Image (MRI)-guided interventions involving percutaneous biopsies of lesions, or trajectory alignment with prospective stereotaxy are conducted in real time using rapid image acquisition. A mechanism of passively localizing a device and calculating its orientation is desired to improve interventional outcomes in these situations. In this work, we propose and evaluate an image-based technique to determine the position and alignment of a linearly shaped interventional device within an ex-vivo tissue specimen. Low resolution 3D orientation scan data is processed to produce a virtual line tting using principal component analysis. The line tting algorithm was incorporated into a biopsy needle tracking system implemented with an MRscanner operated using a footswitch. A GUI application was written to collect foot pedal input and display automated visualization of device placement inside the scanner room. Placement time trials (N=3) conducted with this system using porcine muscle and phantom samples suspended in rigid frames with inserted gadolinium-enhanced targets. The mean targeting error across all directions was 3:6 mm and 5:1 mm for the phantom trials and ex-vivo trials respectively. The average entry-to-target time was 247 sec. Device localization during trials was adequate to contain a 11-gauge titanium biopsy needle within a visualization slice volume of 10 mm after 93:8% of alignments over insertion lengths between 30 mm to 110 mm at insertion angles between 1:4 to 20 from the static magnetic eld and frequency encoding axes. Practical considerations were identi ed and occupational exposure measurements were collected as part of determining the system's overall feasibility.
URI: http://knowledgecommons.lakeheadu.ca/handle/2453/4527
metadata.etd.degree.discipline: Engineering : Electrical and Computer
metadata.etd.degree.name: Master of Science
metadata.etd.degree.level: Master
metadata.dc.contributor.advisor: Pichardo, Samuel
Appears in Collections:Electronic Theses and Dissertations from 2009

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