Faster and Improved 3-D Head Digitization in MEG using Kinect

Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant’s structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we c...

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Main Authors: Santosh eVema Krishna Murthy, Matthew eMacLellan, Steven eBeyea, Timothy eBardouille
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-10-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00326/full
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spelling doaj-9b177cdc54d948379b061aba4cc60d322020-11-24T23:04:33ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2014-10-01810.3389/fnins.2014.00326111014Faster and Improved 3-D Head Digitization in MEG using KinectSantosh eVema Krishna Murthy0Matthew eMacLellan1Steven eBeyea2Steven eBeyea3Timothy eBardouille4Timothy eBardouille5IWK Health CentreIWK Health CentreIWK Health CentreDalhousie UniversityIWK Health CentreDalhousie UniversityAccuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant’s structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices —Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows — for source localization accuracy and MEG-MRI co-registration. A calibrated phantom was used for verifying the source localization accuracy. The Kinect improved source localization accuracy over the Polhemus and the laser scanner by 2.23 mm (137%) and 0.81 mm (50%), respectively. MEG-MRI co-registration accuracy was verified on data from five healthy human participants, who received the digitization process using all three devices. The Kinect device captured approximately 2000 times more surface points than the Polhemus in one third of the time (one minute compared to three minutes) and thrice as many points as the NextEngine laser scanner. Following automated surface matching, the calculated mean MEG-MRI co-registration error for the Kinect was improved by 2.85 mm with respect to the Polhemus device, and equivalent to the laser scanner. Importantly, the Kinect device automatically aligns 20-30 images per second in real-time, reducing the limitations on participant head movement during digitization that are implicit in NextEngine laser scan (~1 minute). We conclude that the Kinect scanner is an effective device for head digitization in MEG, providing the necessary accuracy in source localization and MEG-MRI co-registration, while reducing digitization time.http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00326/fullMagnetoencephalography (MEG)AlignmentHead Position Indicator (HPI)Laser scannerMicrosoft KinectColor recognition
collection DOAJ
language English
format Article
sources DOAJ
author Santosh eVema Krishna Murthy
Matthew eMacLellan
Steven eBeyea
Steven eBeyea
Timothy eBardouille
Timothy eBardouille
spellingShingle Santosh eVema Krishna Murthy
Matthew eMacLellan
Steven eBeyea
Steven eBeyea
Timothy eBardouille
Timothy eBardouille
Faster and Improved 3-D Head Digitization in MEG using Kinect
Frontiers in Neuroscience
Magnetoencephalography (MEG)
Alignment
Head Position Indicator (HPI)
Laser scanner
Microsoft Kinect
Color recognition
author_facet Santosh eVema Krishna Murthy
Matthew eMacLellan
Steven eBeyea
Steven eBeyea
Timothy eBardouille
Timothy eBardouille
author_sort Santosh eVema Krishna Murthy
title Faster and Improved 3-D Head Digitization in MEG using Kinect
title_short Faster and Improved 3-D Head Digitization in MEG using Kinect
title_full Faster and Improved 3-D Head Digitization in MEG using Kinect
title_fullStr Faster and Improved 3-D Head Digitization in MEG using Kinect
title_full_unstemmed Faster and Improved 3-D Head Digitization in MEG using Kinect
title_sort faster and improved 3-d head digitization in meg using kinect
publisher Frontiers Media S.A.
series Frontiers in Neuroscience
issn 1662-453X
publishDate 2014-10-01
description Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant’s structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices —Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows — for source localization accuracy and MEG-MRI co-registration. A calibrated phantom was used for verifying the source localization accuracy. The Kinect improved source localization accuracy over the Polhemus and the laser scanner by 2.23 mm (137%) and 0.81 mm (50%), respectively. MEG-MRI co-registration accuracy was verified on data from five healthy human participants, who received the digitization process using all three devices. The Kinect device captured approximately 2000 times more surface points than the Polhemus in one third of the time (one minute compared to three minutes) and thrice as many points as the NextEngine laser scanner. Following automated surface matching, the calculated mean MEG-MRI co-registration error for the Kinect was improved by 2.85 mm with respect to the Polhemus device, and equivalent to the laser scanner. Importantly, the Kinect device automatically aligns 20-30 images per second in real-time, reducing the limitations on participant head movement during digitization that are implicit in NextEngine laser scan (~1 minute). We conclude that the Kinect scanner is an effective device for head digitization in MEG, providing the necessary accuracy in source localization and MEG-MRI co-registration, while reducing digitization time.
topic Magnetoencephalography (MEG)
Alignment
Head Position Indicator (HPI)
Laser scanner
Microsoft Kinect
Color recognition
url http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00326/full
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