title: Optimization of fMRI-derived ROIs based on coherent functional interaction patterns.
abstract: Accurate localization of functionally meaningful Regions of Interests (ROIs) from fMRI data is critically important to functional brain imaging. A variety of established approaches such as general linear model (GLM) have been widely used in the community. How to determine the optimal location and size of an fMRI-derived ROI, however, remains an open, challenging problem. This paper presents a novel individualized optimization algorithm that simultaneously optimizes the locations and sizes of fMRI-derived ROIs by maximizing the coherences of their functional interaction patterns with respect to the block-based paradigm. As an alternative ROI optimization approach using functional interaction patterns, the algorithm was applied on a working memory task-based fMRI dataset and the experimental results are promising.
authors.affiliation: Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA.
authors.forename: Fan
authors.initials: F
authors.lastname: Deng
authors.forename: Dajiang
authors.initials: D
authors.lastname: Zhu
authors.forename: Tianming
authors.initials: T
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008570:Memory, Short-Term / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity