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Abstract #2206

Automated Intraprocedural Detection and Registration of Interventional Devices via Characteristic Fiducial Markers

Thomas Lilieholm1,2, Jose Guerrero Gonzalez3, Andrew L Alexander1,2,3, Terrence R Oakes2, and Walter F Block1,2,4,5
1Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2ImgGyd, Middleton, WI, United States, 3Waisman Center, University of Wisconsin-Madison, Madison, WI, United States, 4Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 5Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States

Synopsis

Keywords: MR-Guided Interventions, MR-Guided Interventions

Motivation: Image-guided interventions leverage MR-imaging to orient surgical tools relative to internal anatomy. Automated fiducial detection improves workflow efficiency and accuracy relative to manual selection.

Goal(s): To develop and evaluate an autonomous approach for detecting and registering device fiducials during intraprocedural MRI.

Approach: Twelve high-resolution volumetric scans of a trajectory guide with a characteristic fiducial design were acquired. Image processing methods determined the fiducial’s location and orientation.

Results: Across two cadaver and ten phantom scans, automated methods isolated the fiducial 10/12 times, and coregistered it to a template with a Dice coefficient of 0.82 in T2 acquisitions.

Impact: Applied methods were able to leverage geometric information from characteristic fiducial markers to fully autonomously identify and orient a stereotactic trajectory guide, streamlining an often manual or multimodal step in many workflows for MRI-guided interventions.

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Keywords