3D Medical CT Images Reconstruction Based on VTK and Visual C++

In this paper, it is provided to reconstruct three-dimensional(3D) models of human body by using CT slices and digital images and precisely finding locations of pathological formations such as tumours. 3D image CT reconstruction is an attractive field generally in digital image processing techniques, especially in biomedical imaging. It is necessary to incise a 3D object to obtain detail structure information inside in the process of developing 3D medical visualization system. Visual C++ 6.0 with Visualization Toolkit (VTK) toolbox are used to reconstruct 3D images using the CT slice sequence in PAT format. Cuboids that can be controlled to zoom, move or circumrotate by mouse and used for clipping the object of 3D object. Experiment of tooth and foot shows that the technique can realize the real time.

[1]  W A Kalender,et al.  Technical advances in multi-slice spiral CT. , 2000, European journal of radiology.

[2]  Thomas W. Sederberg,et al.  Conversion of complex contour line definitions into polygonal element mosaics , 1978, SIGGRAPH.

[3]  Ahmed S. Abutableb Automatic thresholding of gray-level pictures using two-dimensional entropy , 1989 .

[4]  Martin J. Dürst,et al.  Re , 1988 .

[5]  Yu Xiaohan,et al.  Direct segmentation for 3D medical images , 1993, Proceedings of TENCON '93. IEEE Region 10 International Conference on Computers, Communications and Automation.

[6]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[7]  Henry Fuchs,et al.  Optimal surface reconstruction from planar contours , 1977, SIGGRAPH.

[8]  Eam Khwang Teoh,et al.  A hybrid algorithm for segmentation of range images , 1992, Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation.

[9]  Ahmed S. Abutaleb,et al.  Automatic thresholding of gray-level pictures using two-dimensional entropy , 1989, Comput. Vis. Graph. Image Process..

[10]  D H Brinkmann,et al.  Automated seed localization from CT datasets of the prostate. , 1998, Medical physics.

[11]  A. B. Ekoule,et al.  A triangulation algorithm from arbitrary shaped multiple planar contours , 1991, TOGS.

[12]  Bernd Hamann,et al.  The asymptotic decider: resolving the ambiguity in marching cubes , 1991, Proceeding Visualization '91.

[13]  M. Defrise,et al.  Iterative reconstruction for helical CT: a simulation study. , 1998, Physics in medicine and biology.

[14]  Eric Keppel,et al.  Approximating Complex Surfaces by Triangulation of Contour Lines , 1975, IBM J. Res. Dev..