A surface-based fractal information dimension method for cortical complexity analysis

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Abstract

In this paper, we proposed a new surface-based fractal information dimension (FID) method to quantify the cortical complexity. Unlike the traditional box-counting method to measure the capacity dimension, our method is a surface-based fractal information dimension method, which incorporates surface area into the probability calculation and thus encapsulates more information of the original cortical surfaces. The accuracy of the algorithm was validated via experiments on phantoms. With the proposed method, we studied the abnormalities of the cortical complexity of the early blind (EB; n=15), compared with matched controls (n=15). We found significantly increased FIDs in the left occipital lobe and decreased FIDs in the right frontal and right parietal lobe in early blind compared with controls. The results demonstrated the potential of the proposed method for identifying cortical abnormalities. © 2008 Springer-Verlag Berlin Heidelberg.

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Zhang, Y., Jiang, J., Lin, L., Shi, F., Zhou, Y., Yu, C., … Jiang, T. (2008). A surface-based fractal information dimension method for cortical complexity analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5128 LNCS, pp. 133–141). https://doi.org/10.1007/978-3-540-79982-5_15

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