Application of computer aided 3D simulation technique for complicated foot and ankle fractures

Objective To investigate the effect of computer aided 3D simulation technique for treating complicated foot and ankle fractures precisely.Methods From November 2007 to August 2009,255 patients with complicated foot and ankle fractures

CAD and CAE Integration Through Scientific Visualization Techniques for Illumination Design

Engineers tend to use different software to perform tasks such as geometry modeling, database management, numerical analysis, and visualization. This may cause decrease of productivity and loss of information during the conversion process between different data file formats. This paper presents a computer aided design (CAD) and computer aided engineering (CAE) system integration using scientific visualization tools and techniques. It deals with the development of a 3D CAD add-in for lighting analysis which uses the CAD model as 3D interface for creating a lighting scheme, processing, and visualizing 2D or 3D illuminance fields. Visualization features as color and contour mapping were developed using the visualization toolkit (VTK) toolkit. The application integrates all functionalities of the 3D CAD with tools for light sources database management, pre-processing, processing, and post-processing of illuminance fields in a single environment. This approach increases productivity and eliminates the need for different software.

STEP-based Feature Recognition System for B-spline Surface Features

The geometrical and topological information of 3D computer aided design （CAD） models should be represented as a neut- ral format file to exchange the data between different CAD systems. Exchange of 3D CAD model data implies that the companies must exchange complete information about their products, all the way from design, manufacturing to inspection and shipping. This informa- tion should be available to each relevant partner over the entire life cycle of the product. This led to the development of an international standard organization （ISO） neutral format file named as standard for the exchange of product model data （STEP）. It has been ob- served from the literature, the feature recognition systems developed were identified as planar, cylindrical, conical and to some extent spherical and toroidal surfaces. The advanced surface features such as B-spline and its subtypes are not identified. Therefore, in this work, a STEP-based feature recognition system is developed to recognize t--spline surface features and its sub-types from the 3D CAD model represented in AP203 neutral file format. The developed feature recognition system is implemented in Java programming language and the product model data represented in STEP AP203 format is interpreted through Java standard data access interface （JSDAI）. The developed system could recognize B-spline surface features such as B-Spline surface with knots, quasi uniform surface, uniform surface, rational surface and Bezier surface. The application of extracted B-spline surface features information is discussed with reference to the toolpath generation for STEP-NC （STEP AP238）.

Computer-aided 3-D reconstruction and measurement of the optic canal and intracanalicular structures

Objective To reconstruct the human optic canal and its inner structures, and to provide detailed knowledge of this region for optic nerve decompression for further understanding on the pathologic mechanisms of indirect optic nerve injury Methods Six optic canals and their inner structures were reconstructed using a computer aided 3 dimensional reconstruction system Quantitative measurement of the canal wall thickness, bony canal transverse area, optic nerve transverse area, dural sheath transverse area, subarachnoid space transverse area, and subarachnoid space volume were done by means of the computer morphometric analysis system The detailed spatial relationship among intracanalicular structures were also carefully identified on the 3 D models Results The thinnest portion of the canal was the middle part of the medial wall (0 45±0 35?mm) and the narrowest space was in the middle part of the optic canal (the transverse area was 18 21±2 50?mm 2) The volume of subarachnoid space which can be considered the compensatory space for distention incurred by the hemorrhage, optic nerve edema, or hematoma was 21 16±4 31?mm 3 At the cranial opening ,the middle part and orbital opening, its transverse area was 4 45±1 12?mm 2, 2 68±1 32?mm 2 and 1 23±0 83?mm 2, respectively Conclusions Since the compensatory space was limited, even a tiny amount of blood or swelling of the nerve may cause optic nerve compression Because the narrowest space was in the middle part of the optic canal and the compensatory space for distention gradually decreases from cranial end to orbital end, the middle part and the anterior part of the optic canal and dural sheath are critical in optic nerve decompression