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.
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Deng, F., Zhu, D., Liu, T. (2012). Optimization of fMRI-Derived ROIs Based on Coherent Functional Interaction Patterns. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33454-2_27
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DOI: https://doi.org/10.1007/978-3-642-33454-2_27
Publisher Name: Springer, Berlin, Heidelberg
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