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In this paper, segmentation techniques depending on T-ray CT functional imaging are investigated. A set of linear image fusion and novel wavelet scale correlation segmentation techniques are adopted in order to achieve classification within 3D objects. The methods are applied to a T-ray CT image dataset of a glass vial containing a plastic tube. This experiment simulates the imaging of a simple nested organic structure, which will provide an indication of the potential for using T-ray CT imaging to achieve T-ray pulsed signal classification of heterogeneous layers.