Issue No. 01 - January/February (2010 vol. 30)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2010.12
Christopher Koehler , Wright State University
Thomas Wischgoll , Wright State University
These knowledge-assisted 3D rib cage and lung reconstruction algorithms mimic some of the useful features of CT scans to facilitate early detection of diseases such as lung cancer, at a fraction of the cost. The reconstructions are based on the typical posterior-anterior and lateral x-ray images that are acquired during preemptive screenings for lung cancer. Combining shared domain knowledge of human anatomy and solid-modeling techniques with the information that computer vision algorithms automatically extract from these x-ray images, this interactive approach transforms a series of primitive template meshes into reconstructed ribs and lungs, even though much of the 3D information is lost during the x-ray process. An example illustrates how using the reconstructed lung geometry to clip a portion of an approximate volume reconstruction can provide a supplementary interface to search for potential diseased areas. This article is part of a special issue on knowledge-assisted visualization.
3D reconstruction, segmentation, rib cage reconstruction, lung reconstruction, x-ray, computer graphics, graphics and multimedia
T. Wischgoll and C. Koehler, "Knowledge-Assisted Reconstruction of the Human Rib Cage and Lungs," in IEEE Computer Graphics and Applications, vol. 30, no. , pp. 17-29, 2010.