Meeting Banner
Abstract #2708

Decomposing cerebral blood flow MRI into functional and structural components

Benjamin Kandel 1,2 , James C. Gee 3 , Jiongjiong Wang 4 , and Brian B Avants 3

1 Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, 2 Penn Image Computing and Science Laboratory, Philadelphia, PA, United States, 3 Penn Image Computing and Science Laboratory, University of Pennsylvania, PA, United States, 4 University of California Los Angeles, CA, United States

Cerebral blood flow (CBF) is partially determined by brain structure. Current methods for analyzing CBF imaging techniques, such as arterial spin labeling, only take into account limited anatomical information. We propose a method that uses a dictionary learning approach to provide a more rigorous decomposition of CBF images into a component that can be predicted by structural information and a "purely functional" component that cannot be predicted using brain structure. This technique has shown to predict a greater proportion of CBF than segmentation maps, and can be used for assessing the relative contributions of CBF and structural imaging.

This abstract and the presentation materials are available to members only; a login is required.

Join Here