A systematic comparison of structural, structural connectivity, and functional connectivity based thalamus parcellation techniques
Charles Iglehart (1), Martin Monti (2, 3), Joshua Cain (2), Thomas, Tourdias (4), Manojkumar Saranathan (1, 5) ((1) Department of Electrical, and Computer Engineering, University of Arizona, Tucson, Arizona, United, States, (2) Department of Psychology

TL;DR
This paper systematically compares structural, diffusion, and functional MRI-based methods for thalamus segmentation, revealing that functional connectivity-based parcellation closely aligns with structural methods and the Morel atlas.
Contribution
It provides the first comprehensive comparison of different MRI-based thalamic segmentation techniques on the same dataset.
Findings
Functional connectivity-based parcellation closely matches structural methods.
Quantitative measures show high concordance with the Morel atlas.
The study highlights the potential of functional MRI for accurate thalamic segmentation.
Abstract
The thalamus consists of several histologically and functionally distinct nuclei increasingly implicated in brain pathology and important for treatment, motivating the need for development of fast and accurate thalamic segmentation. The contrast between thalamic nuclei as well as between the thalamus and surrounding tissues is poor in T1 and T2 weighted magnetic resonance imaging (MRI), inhibiting efforts to date to segment the thalamus using standard clinical MRI. Automatic segmentation techniques have been developed to leverage thalamic features better captured by advanced MRI methods, including magnetization prepared rapid acquisition gradient echo (MP-RAGE) , diffusion tensor imaging (DTI), and resting state functional MRI (fMRI). Despite operating on fundamentally different image features, these methods claim a high degree of agreement with the Morel stereotactic atlas of the…
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