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Proceedings Paper

Three-dimensional medical reconstruction by using local statistic feature-based classification
Author(s): Jiawan Zhang; Jizhou Sun
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Paper Abstract

Three-dimensional volume reconstruction has gained great popularity as a powerful technique for the visualization of volume datasets such as those obtained from X-ray, computed tomography, and magnetic resonance imaging in recent years. Local features play important part in the classification process for a variety of medical image analysis, computer-aided diagnosis, and three-dimensional reconstruction and visualization applications. By using high-order local statistic features detected by local block based moments, such as flat, round, elongated shapes, together with the local spectral histogram of textures, to act as classification criteria, a three-dimensional medical reconstruction method is proposed in this paper. A volume splatting algorithm by using the proposed classification method is implemented and relatively high-quality rendering results can be obtained when the proposed method is applied in medical reconstructions.

Paper Details

Date Published: 25 September 2003
PDF: 5 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.538643
Show Author Affiliations
Jiawan Zhang, Tianjin Univ. (China)
Jizhou Sun, Tianjin Univ. (China)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition

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