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Diffeomorphic brain mapping based on T1‐weighted images: Improvement of registration accuracy by multichannel mapping
Author(s) -
Djamanakova Aigerim,
Faria Andreia V.,
Hsu John,
Ceritoglu Can,
Oishi Kenichi,
Miller Michael I.,
Hillis Argye E.,
Mori Susumu
Publication year - 2013
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.23790
Subject(s) - artificial intelligence , computer science , image registration , computer vision , diffeomorphism , pattern recognition (psychology) , mathematics , image (mathematics) , mathematical analysis
Purpose: To improve image registration accuracy in neurodegenerative populations. Materials and Methods: This study used primary progressive aphasia, aged control, and young control T1‐weighted images. Mapping to a template image was performed using single‐channel Large Deformation Diffeomorphic Metric Mapping (LDDMM), a dual‐channel method with ventricular anatomy in the second channel, and a dual‐channel with appendage method, which utilized a priori knowledge of template ventricular anatomy in the deformable atlas. Results: Our results indicated substantial improvement in the registration accuracy over single‐contrast‐based brain mapping, mainly in the lateral ventricles and regions surrounding them. Dual‐channel mapping significantly ( P < 0.001) reduced the number of misclassified lateral ventricle voxels (based on a manually defined reference) over single‐channel mapping. The dual‐channel (w/appendage) method further reduced ( P < 0.001) misclassification over the dual‐channel method, indicating that the appendage provides more accurate anatomical correspondence for deformation. Conclusion: Brain anatomical mapping by shape normalization is widely used for quantitative anatomical analysis. However, in many geriatric and neurodegenerative disorders, severe tissue atrophy poses a unique challenge for accurate mapping of voxels, especially around the lateral ventricles. In this study we demonstrate our ability to improve mapping accuracy by incorporating ventricular anatomy in LDDMM and by utilizing a priori knowledge of ventricular anatomy in the deformable atlas. J. Magn. Reson. Imaging 2013;37:76–84. © 2012 Wiley Periodicals, Inc.