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Motion Detection and Tracking of Mobile Tissue-Equivalent Phantoms Using a Microwave Imaging System

M Afify1*, , I Ali2 , S Ahmad2 , N Alsbou1, (1) Department of Engineering and Physics, University of Central Oklahoma, Edmond, OK, (2) University of Oklahoma Health Sciences Center, Oklahoma City, OK,


(Tuesday, 7/16/2019) 7:30 AM - 9:30 AM

Room: 225BCD

Purpose: To develop a microwave motion detection system for detecting and sorting phantom motion by measuring variations in the microwave signal and also a motion classification model to use the variations in the microwave signal extracting 3D-motion parameters for tissue equivalent phantoms in the microwave field-of-view.

Methods: A microwave system that is made from a transmitter and receiver with 10.25 GHz was used to detect phantom motion. Different tissue equivalent phantoms with a mobile platform moved with different motion patterns were used to test this microwave motion detection system. The variations of the microwave signal with phantom position, thickness and density were quantified. A motion classification algorithm was developed that used microwave intensity variations correlated with changes of phantom position, volume and density to extract motion parameters. This algorithm corrects for wave artifact that include air attenuation, interference, polarization affecting the microwave intensity measured by the receiver.

Results: The position of the minimal intensity of the microwave signal detected by the receiver varied linearly with the positon of the phantom in the microwave field-of-view which can be predicted within 0.5 mm. The microwave intensity varied non-linearly with the density of phantoms equivalent to bone, lung, breast muscle, adipose, liver tissues. The microwave intensity decreased non-linearly with the increase in phantom thickness (1 mm). These parameters were classified to extract the motion parameters of a mobile phantom. This microwave system tracks variations in the position, volume and density of the phantom in the field-of-view instead of tracking external or internal markers.

Conclusion: This microwave motion detection system was able to detect variations in position, thickness and density of mobile phantoms demonstrating potential clinical applications in medical imaging; and in cancer patient treatments using radiation therapy with motion management that are superior to tracking external or internal markers.


Microwaves, Respiration, Gating


TH- RT Interfraction motion management : Development (new technology and techniques)

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