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9 January 2015 Comparison of procedures for co-registering scalp-recording locations to anatomical magnetic resonance images
Antonio M. Chiarelli, Edward L. Maclin, Kathy A. Low, Monica Fabiani, Gabriele Gratton
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Journal of Biomedical Optics, Vol. 20, Issue 1, 016009 (January 2015). https://doi.org/10.1117/1.JBO.20.1.016009
Abstract
Functional brain imaging techniques require accurate co-registration to anatomical images to precisely identify the areas being activated. Many of them, including diffuse optical imaging, rely on scalp-placed recording sensors. Fiducial alignment is an effective and rapid method for co-registering scalp sensors onto anatomy, but is quite sensitive to placement errors. Surface Euclidean distance minimization using the Levenberq-Marquart algorithm (LMA) has been shown to be very accurate when based on good initial guesses, such as precise fiducial alignment, but its accuracy drops substantially with fiducial placement errors. Here we compared fiducial and LMA co-registration methods to a new procedure, the iterative closest point-to-plane (ICP2P) method, using simulated and real data. An advantage of ICP2P is that it eliminates the need to identify fiducials and is, therefore, entirely automatic. We show that, typically, ICP2P is as accurate as fiducial-based LMA, but is less sensitive to initial placement errors. However, ICP2P is more sensitive to spatially correlated noise in the description of the head surface. Hence, the best technique for co-registration depends on the type of data available to describe the scalp and the surface defined by the recording sensors. Under optimal conditions, co-registration error using surface-fitting procedures can be reduced to ∼3  mm.
© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2015/$25.00 © 2015 SPIE
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Antonio M. Chiarelli, Edward L. Maclin, Kathy A. Low, Monica Fabiani, and Gabriele Gratton "Comparison of procedures for co-registering scalp-recording locations to anatomical magnetic resonance images," Journal of Biomedical Optics 20(1), 016009 (9 January 2015). https://doi.org/10.1117/1.JBO.20.1.016009
Published: 9 January 2015
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Cited by 31 scholarly publications.
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KEYWORDS
Magnetic resonance imaging
Head
Sensors
Tellurium
Error analysis
Image segmentation
Absorption
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