Hepatic vessel segmentation from computed tomography using three-dimensional hyper-complex edge detection operator
Yang Ma, Xingmin Li · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
This paper proposes a three-dimensional(3D) segmentation algorithm using hyper-complex edge detection operator and applies the new algorithm to three-dimensional hepatic vessel segmentation from computed tomography (CT) volumetric data. A 3D hyper-complex edge detection operator is constructed by combining octonion and gradient operator. We replace every voxel of the volumetric data by one octonion which consist of its gray-level and its 6 neighborhoods' gray-level. Via this the original volumetric data is defined as octonion volumetric data. Similar to the Sobel operator, there are three principal directions (coordinate axes) in 3D hyper-complex edge detection operator, and each element in this operator is a octonion. The operator is circularly convoluted with octonion volumetric data to get the value of matching response. If matched, this voxel is the edge of vessel. Experimental results show that the algorithm can effectively segment small vascular tree branches.