Intersubject coregistration of brain images: a phantom study

Henry Rusinek; Wai-Hon Tsui; Michael Sanfilipo; Adam Wolkin

doi:10.1117/12.310926

24 June 1998 Intersubject coregistration of brain images: a phantom study

Henry Rusinek, Wai-Hon Tsui, Michael Sanfilipo, Adam Wolkin

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310926
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

Inter-subject coregistration is a powerful neuroimaging technique that enables comparison and detection of morphological differences across groups of subjects. The present study uses digital phantoms to evaluate errors in two widely employed approaches to inter-subject coregistration of structural MR images of the brain: the manual step-wise approach and the automated method provided with the software package SPM96. Phantoms were constructed by deforming a high resolution T1-weighted MR image in which we have embedded 12 landmarks. For the manual method the accuracy ranged from 0.8 mm in quadrigeminal plate to 2.4 mm in superior central sulcus and occipital lobe. The average error was 1.5 mm. For the automated SPM96 method and the 9 parameter model, the accuracy ranged from 0.8 mm to 2.1 mm and averaged 1.1 mm. Error of the manual method correlated strongly with the distance from the center of the image (r equals 0.77, slope equals .020, p equals .003). The linear correlation of the error obtained with the automated method with the distance was poor (r equals 0.39, slope equals .008, p > 0.2). The results suggest that the inferior performance of the manual method is due to its step-wise approach and to a relatively large rotational error.

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Henry Rusinek, Wai-Hon Tsui, Michael Sanfilipo, and Adam Wolkin "Intersubject coregistration of brain images: a phantom study", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310926

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KEYWORDS

Brain

Neuroimaging

Magnetic resonance imaging

Error analysis

Affine motion model

3D image processing

Image segmentation

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