Intersubject brain image registration using both cortical and subcortical landmarks

Yaorong Ge; J. Michael Fitzpatrick; Robert M. Kessler; Magdelena Jeske-Janicka; Richard A. Margolin

doi:10.1117/12.208681

12 May 1995 Intersubject brain image registration using both cortical and subcortical landmarks

Yaorong Ge, J. Michael Fitzpatrick, Robert M. Kessler, Magdelena Jeske-Janicka, Richard A. Margolin

Proceedings Volume 2434, Medical Imaging 1995: Image Processing; (1995) https://doi.org/10.1117/12.208681
Event: Medical Imaging 1995, 1995, San Diego, CA, United States

Abstract

Intersubject registration of brain images involves localizing a set of easily detectable common features, matching these features, and finding a transformation that establishes a one-to-one correspondence of two image volumes from different subjects. Several different features and different methods for finding transformations have been described in the literature. A drawback common to the existing methods is that no, or few, features in the brain cortex are used. This paper studies the importance of incorporating such landmarks in brain registration. We apply a previously reported method to localize cortical convolutions in magnetic resonance images. We then derive a set of cortical landmarks from the traces representing the localized convolutions. Adding these cortical landmarks to a set of primarily subcortical landmarks proposed in an existing method, we compute matching transformations using a three dimensional thin-plate spline. Experiments comparing our method with a linear scaling method as well as an existing method that uses the previously proposed landmarks show that our method with the addition of cortical landmarks dramatically improves the registration quality in the cortex region.

Citation Download Citation

Yaorong Ge, J. Michael Fitzpatrick, Robert M. Kessler, Magdelena Jeske-Janicka, and Richard A. Margolin "Intersubject brain image registration using both cortical and subcortical landmarks", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); https://doi.org/10.1117/12.208681

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