Decomposing cerebral blood flow MRI into functional and structural components: a non-local approach based on prediction.

ABSTRACT: We present RIPMMARC (Rotation Invariant Patch-based Multi-Modality Analysis aRChitecture), a flexible and widely applicable method for extracting information unique to a given modality from a multi-modal data set. We use RIPMMARC to improve the interpretation of arterial spin labeling (ASL) perfusion images by removing the component of perfusion that is predicted by the underlying anatomy. Using patch-based, rotation invariant descriptors derived from the anatomical image, we learn a predictive relationship between local neuroanatomical structure and the corresponding perfusion image. This relation allows us to produce an image of perfusion that would be predicted given only the underlying anatomy and a residual image that represents perfusion information that cannot be predicted by anatom

SUBMITTER: Kandel BM 

PROVIDER: S-EPMC4356637 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature