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Real-time Head Motion Tracking for Brain Positron Emission Tomography using Microsoft Kinect V2

The scope of the current research work was to evaluate the potential of the latest version of Microsoft Kinect sensor (Kinect v2) as an external tracking device for head motion during brain imaging with brain Positron Emission Tomography (PET). Head movements constitute a serious degradation factor in the acquired PET images. Although there are algorithms implementing motion correction using known motion data, the lack of effective and reliable motion tracking hardware has prevented their widespread adoption. Thus, the development of effective external tracking instrumentation is a necessity. Kinect was tested both for Siemens High-Resolution Research Tomograph (HRRT) and for Siemens ECAT HR PET system. The face Application Programming Interface (API) ’HD face’ released by Microsoft in June 2015 was modified and used in Matlab environment. Multiple experimental sessions took place examining the head tracking accuracy of kinect both in translational and rotational movements of the head. The results were analyzed statistically using one-sample Ttests with the significance level set to 5%. It was found that kinect v2 can track the head with a mean spatial accuracy of µ0 < 1 mm (SD = 0,8 mm) in the y-direction of the tomograph’s camera, µ0 < 3 mm (SD = 1,5 mm) in the z-direction of the tomograph’s camera and µ0 < 1 ◦ (SD < 1 ◦ ) for all the angles. However, further validation needs to take place. Modifications are needed in order for kinect to be used when acquiring PET data with the HRRT system. The small size of HRRT’s gantry (over 30 cm in diameter) makes kinect’s tracking unstable when the whole head is inside the gantry. On the other hand, Kinect could be used to track the motion of the head inside the gantry of the HR system.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-189973
Date January 2016
CreatorsTsakiraki, Eleni
PublisherKTH, Skolan för teknik och hälsa (STH)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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