SegMo: CT volume segmentation using a multi-level Morse complex. (February 2019) - Nagai, Yukie; Ohtake, Yutaka; Suzuki, Hiromasa
Abstract: The analysis of existing objects for developing new products is called reverse engineering and is a common process in industrial manufacturing. X-ray CT scanning is a powerful reverse-engineering tool that can acquire the entire geometry of an assembled object, including its inner structure, without disassembly. Before X-ray CT scanning can be used to accurately extract the parts of an assembled object from its CT volume, several challenges remain: CT artifacts, the non-uniqueness of the CT values, and limited resolution. Currently, an operator usually manually segments the target parts of the CT volume at voxel-level accuracy, which takes a long time. Hence, this paper proposes SegMo, a segmentation system which can perform segmentation of an assembled object to sub-voxel accuracy more quickly and with less effort than conventional methods. These advantages are achieved by suggesting the part boundary candidates that are coded as a hierarchical decomposition of the CT volume based on a Morse complex and polygonization at sub-voxel accuracy. SegMo consists of three steps: the generation of a hierarchical decomposition of a CT volume, segmentation using this hierarchy, and polygonization of the segmentation result. In this paper, we demonstrate how SegMo can achieve accurate and efficient segmentation on CT volumes of several complex assembled objects. Highlights: Practical segmentation system for X-ray CT volumes of assembles is proposed. Accurate surface mesh of each segmented part can be obtained. GUI assisting the efficiency of manual operation is proposed. Examples of segmentation with CT volumes of complex object are shown.