In this paper, we demonstrated that tumors in freshly excised whole brain tissue could be differentiated clearly from normal brain tissue using a homemade continuous terahertz (THz) wave attenuated total reflection (ATR) imaging system. The resolution of this system was about 400μm×450μm at 2.52THz. The terahertz images characters of fresh brains with tumor was studied using this THz-ATR imaging system. Tumor regions could be differentiated clearly from normal brain tissue by THz intensity imaging at different frequencies. The high absorption regions in THz images corresponded well to the tumor regions in the hematoxylin and eosin-stained microscopic images. Moreover, the morphological reconstruction method was applied to restore the blurred imaging results. The noise caused by power fluctuation in THz-ATR image was almost eliminated and the visibility of objects has been successfully enhanced. These promising results suggest that THz-ATR imaging could be used as a tool for label-free and real-time imaging of brain tumors, which would be great potential as an alternative method for the fast diagnosis tumor region during brain surgery.
Region of interest segmentation is essential for computer aided application of THz imaging. However, THz images is severely degraded by motion blur, poor resolution and noise. A robust, accurate and time-saving algorithm is in dire need for the ROI segmentation of THz images. Recently, ROI segmentation of THz-TDS images and passive THz images has been widely studied. While the ROI segmentation of THz continuous wave (CW) image is still in its infancy. In this paper, we proposed a hybrid ROI segmentation method for THz CW images. The hybrid method combines block match 3D denoising, fuzzy c-means clustering, morphology operation and canny edge detection. The hybrid method is implemented to two images acquired with a THz CW reflection imaging system. To evaluate the performance of our algorithm, we calculated the accuracy, sensitivity and specificity. As the result indicates, this hybrid ROI segmentation method performs well for THz images.
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