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Session: Tracking Strategies [Return to Session]

Three-Dimensional Voxel-By-Voxel Motion Tracking of Mobile Phantoms Using Microwave Imaging

N Alsbou1*, S Ahmad2, I Ali2, (1) Department of Engineering and Physics, University of Central Oklahoma, Edmond, OK, (2) University of Oklahoma Health Sciences Center, Oklahoma City, OK

Presentations

MO-H345-IePD-F5-3 (Monday, 7/11/2022) 3:45 PM - 4:15 PM [Eastern Time (GMT-4)]

Exhibit Hall | Forum 5

Purpose: To track the motion of mobile phantom manufactured from tissue equivalent materials using microwave-imaging. A motion tracking model was developed that uses the variation in the microwave signal to classify the microwave signals and extract 3D-motion trajectory on a voxel-by-voxel basis for the whole phantom volume in the microwave imaging view.

Methods: Several microwave motion sensors were mounted in a circular ring around a mobile phantom that moves with controlled motion patterns. A sequence of 2D and 3D-microwave images were acquired and sorted in time to create the motion trajectory for of all the voxels in the tissue-equivalent phantom. The variations in the microwave intensity due to variations in phantom position, thickness and density were classified to quantify the motion parameters induced by different motion patterns that mimic variation in amplitude and frequency in respiratory motion of different patients.

Results: The motion trajectory of a mobile phantom was reconstructed using microwave-imaging and a classification motion algorithm. The motion algorithm classified the relationship between the variations in microwave intensity and the mobile phantom positon, thickness, and composition in the imaging field of view. The variations in the position of the different voxels varied linearly with the positon of the minimal microwave intensity within 3.0mm. The minimal microwave intensity deceased nearly linearly with the increasing volume of water in the microwave imaging field. However, variations in the microwave intensity was not linear with the density of the tissue-equivalent phantom objects such as breast, muscle, liver adipose, lung and bone.

Conclusion: Using microwave-imaging, a voxel-by-voxel motion detection technique for the whole volume of a tissue-equivalent phantom was developed. This technique has potential clinical application particularly in radiation therapy considering tracking all voxels in the image instead of tracking an external or internal-markers used in gating from the management of cancer patient motion.

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