System and method for colon unfolding via skeletal subspace deformation

#The present invention relates generally to the field of imaging apparatus and more particularly to facilitating the unfolding or surface development of generally tubular structures such as, by way of example, the colon and other generally tubular anatomical organs.

#Virtual colonoscopy is a non-invasive screening procedure aimed at exploring the inner colonic surface, typically in a search for lesions. Standard methods in virtual colonoscopy generally try to simulate conventional colonoscopy techniques by using “virtual fly-throughs” of the reconstructed colon image. Major problems associated with such techniques include the time required to navigate through the complex colon shape and the number of areas that are often inadvertently left uninspected as they remain occluded behind Haustral folds. A number of techniques have been proposed to alleviate these problems, including utilizing Mercator projections (see, for example, Paik, D., Beaulieu, C, Jeffrey, R. C. A., Karadi, C, S., Napel, S., “Visualization modes for CT colonography using Cylindrical and planar map projections”, J. Comput Assist. Tomogr. vol. 24(2), pp. 179-188 (2000)); an unfolded cube display (see, for example, Vos, F., Serlie, I., van Gelder, R., Post, F. Truyen, R., Gerritsen, F., Stoker, J., Vossepoel, A., A New Visualization Method for Virtual Colonoscopy, MICCAI 2001: 645-654, (2001)); and panoramic projections (see, for example, Geiger, B., Chefd'hotel, C, Sudarsky, S., Panoramic Views for Virtual Endoscopy, Duncan, J, Gerig, G. (eds), MICCAI 2005, LNCS 3749, 662-669, Springer-Verlag, (2005)).

#Recently, an alternative approach has emerged in the literature which proposes the use of virtual dissection of the colonic surface to speed up the inspection process. With this technique, the 3D model of the colon is cut open longitudinally and displayed as a single flat image. This approach has the potential of decreasing the inspection time and at the same time reducing the number of blind areas. However, it is well known that the colon lumen cannot be flattened onto a plane without introducing some deformations. See Johnson K., Johnson C., Fletcher, J., MacCarty, R., Summers, R., CT colonography using 360-degree virtual dissection: a feasibility study. AJR Am J Roentgenol; 186:90-95, (2006).

#The invention will be more fully understood from the following detailed description, in conjunction with the drawing, in which

#FIG. 1 shows in block schematic form steps of the virtual dissection process in accordance with principles of the invention;

#FIG. 2, in diagrammatic form, shows in FIG. 2A center line segments with corresponding coordinate systems in accordance with principles of the invention, and shows in FIG. 2B nearest centerline points before and after applying a smoothing step in accordance with principles of the invention;

#It is an object of the present invention to provide a system and method for digitally straightening a colon image in a manner significantly faster than prior techniques. Typically, in accordance with the principles of the present invention, a complete unfolding can be generated in under two minutes.

#There follows a description in detail of an algorithm in conjunction with exemplary embodiments in accordance with the present invention, generally following the outline shown in FIG. 1. In the block schematic of FIG. 1, given a CT data volume 2, we compute a fully automated colon segmentation based on a threshold region growing operation, at step 4. Centerline computation of the colon is performed in step 6, followed by a distance map computation in step 8. In a parallel path following colon segmentation in step 4, a polyhedral generation is performed in step 10. The results of steps 8 and 10 are utilized in step 12 for carrying out colon straightening, and in step 14 dissection image computation is performed.

#Segmentation in organ imaging for identifying and displaying specific structures in volume data sets is an established field in which numerous well-known techniques are utilized. Detailed descriptions of the principles involved and a number of such techniques are available in standard textbooks and numerous journal articles. For further detail, reference is hereby made for incorporation of applicable teachings under segmentation in, for example, A. R. Weeks, Jr., Fundamentals of Image Processing, (Chapter 8), SPIE/IEEE Series on Imaging Science & Engineering, 1996; R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall, Inc., second edition 2002.; T. S. Yoo, Insight into Images, A. K. Peters, Wellesley, Mass., 2004; M. Sonka, V. Hlavac, R. Boyle, Image Processing, Analysis, and Machine Vision, Brooks/Cole Publishing Company, second edition 999; P. Rogalla et al., Editors, Virtual Endoscopy and Related 3D Topics, Springer-Verlag, 2002.