3D segmentation of medical images for computer-aided design and rapid prototyping of orthopedic devices

Justin R. Kidder; Bartholomew O. Nnaji

doi:10.1117/12.298004

2 January 1998 3D segmentation of medical images for computer-aided design and rapid prototyping of orthopedic devices

Justin R. Kidder, Bartholomew O. Nnaji

Proceedings Volume 3201, Sensors and Controls for Advanced Manufacturing; (1998) https://doi.org/10.1117/12.298004
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States

Abstract

The segmentation of medial images is the first step along the series of events that need to take place during the automated design and rapid prototyping of orthopedic devices. The segmentation algorithm presented in this work, the discrete surface model, is an automated 3D segmentation method that attempts to optimize an energy function based on three distinct potentials: a deformation potential that expands the model, an image potential that causes it to stop at image boundaries, and a topology potential that maintains a smooth curvature. Since the deformation of the discrete surface model is local in nature, a global optimization routine encapsulates the deformation of the model using simulated annealing to avoid local energy minima such as are caused by false edges. In addition, the model has no inherent way of checking for self intersections. Global topology is also maintained using a ray-shooting technique that prevents self intersections for occurring in concave models. This segmentation algorithm is ideal for the creation of physical 3D models using rapid prototyping.

Citation Download Citation

Justin R. Kidder and Bartholomew O. Nnaji "3D segmentation of medical images for computer-aided design and rapid prototyping of orthopedic devices", Proc. SPIE 3201, Sensors and Controls for Advanced Manufacturing, (2 January 1998); https://doi.org/10.1117/12.298004

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