A new automatic surface reconstruction algorithm for generating a polygonal mesh from three-dimensional biomedical image scan information using image processing and graph theory

Computed Tomography (CT) imaging is commonly used by physicians to assess problems in the skeleton, head and neck. A CT scanner produces a series of two-dimensional (2D) planar slices that may be stacked together to form what is essentially a three-dimensional (3D) X-ray. It is not feasible to directly view a 3D CT volume with the visualization technology that is currently available. What is currently needed is a method to accurately convert selective information in these volumes into a series of 2D images that can be viewed on a normal computer screen, while providing a sense of 3D realism. This can be accomplished by using a process called 3D Reconstruction.;One commonly used 3D Reconstruction technique, called Surface Reconstruction, involves generating a 3D polygonal mesh that describes a particular surface within the imaged object, such as bone or soft tissue. Biomedical polygonal meshes can be used for a variety of diagnostic and planning applications such as surgical planning for facial reconstruction, custom joint implant design, and radiation therapy planning.;This dissertation describes an innovative Surface Reconstruction technique which preserves the detail in the 3D information and provides the accuracy necessary for medical applications. This technique uses a variety of concepts from Computer Graphics, Image Processing, and Graph Theory.