Layered manufacturing for medical imaging data

摘要

Layered manufacturing techniques have been successfully employed to construct scanned objects from three-dimensionalmedical image data sets. The printed physical models are useful tools for anatomical exploration, surgical planning, teaching, and related medical applications. Before fabricating scanned objects, we have to first build watertight geometricalrepresentations of the target objects from medical image data sets. Many algorithms had been developed to fulfill thisduty. However, some of these methods require extra efforts to resolve ambiguity problems and to fix broken surfaces.Other methods cannot generate legitimate models for layered manufacturing. To alleviate these problems, this articlepresents a modeling procedure to efficiently create geometrical representations of objects from computerized tomography scan and magnetic resonance imaging data sets. The proposed procedure extracts the iso-surface of the targetobject from the input data set at the first step. Then it converts the iso-surface into a three-dimensional image and filtersthis three-dimensional image using morphological operators to remove dangling parts and noises. At the next step, a distance field is computed in the three-dimensional image space to approximate the surface of the target object. Then theproposed procedure smooths the distance field to soothe sharp corners and edges of the target object. Finally, a boundary representation is built from the distance field to model the target object. Compared with conventional modelingtechniques, the proposed method possesses the following advantages: (1) it reduces human efforts involved in the geometrical modeling process. (2) It can construct both solid and hollow models for the target object, and wall thickness ofthe hollow models is adjustable. (3) The resultant boundary representation guarantees to form a watertight solid geometry, which is printable using three-dimensional printers. (4) The proposed procedure allows users to tune the precisionof the geometrical model to compromise with the available computational resources.