GPF Deformable Model based Vessel Segmentation in CT
Xianghua Xie · 2012
In this work, we present a method to segment carotid vessels from CT scans. Image denoising is performed using vessel enhancing diffusion, which can smooth out image noise and enhance vessel structures. The Canny edge detection technique which produces object edges with single pixel width is used for accurate detection of the lumen boundaries. The image gradients are then used to compute the geometric potential field which gives a global representation of the geometric configuration. The deformable model uses a regional constraint to suppress calcified regions for accurate segmentation of the vessel geometries. The preliminary result shows the prosed method achieves promising results based on qualitative evaluation using manual labelled groundtruth.