A novel morphological approach to volume extraction in 3D tomography

Extracting a region of interest from volumetric data represents an important task in the field of digital image analysis. Several approaches to this problem are proposed in literature. The present paper affords volume extraction for regions of interest whose characteristics are not known a-priori. This is the case, for instance, of cancerous tissues in medical tomography or defects in industrial tomography. The technique here described allows extraction of completely arbitrary shapes with a minimum interaction with the user. The volume of interest is defined through the semi-automatic selection of a small set of rail contours at different planes. Such contours are then blended through a morphing technique in order to interpolate the cutting surface. The overall technique demonstrates to be intuitive, efficient and robust. Some results are reported where the method has been applied to micro-tomographic measurements.