For electrical impedance tomography (EIT) of brain, the use of anatomically accurate and patient-specific finite
element (FE) mesh has been shown to confer significant improvements in the quality of image reconstruction. But, given
the lack of a rapid method to achieve the accurate anatomic geometry of the head, the generation of patient-specifc mesh
is time-comsuming. In this paper, a modified fuzzy c-means algorithm based on non-local means method is performed to
implement the segmentation of different layers in the head based on head CT images. This algorithm showed a better
effect, especially an accurate recognition of the ventricles and a suitable performance dealing with noise. And the FE
mesh established according to the segmentation results is validated in computational simulation. So a rapid practicable
method can be provided for the generation of patient-specific FE mesh of the human head that is suitable for brain EIT.
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