Paper
20 May 1999 Extraction and analysis of large vascular networks in 3D micro-CT images
Author Affiliations +
Abstract
High-resolution micro-CT scanners permit the generation of three-dimensional (3D) digital images containing extensive vascular networks. These images provide data needed to study the overall structure and function of such complex networks. Unfortunately, human operators have extreme difficulty in extracting the hundreds of vascular segments contained in the images. Also, no suitable network representation exists that permits straightforward structural analysis and information retrieval. This work proposes an automatic procedure for extracting and analyzing the vascular network contained in very large 3D CT images, such as can be generated by 3D micro- CT and by helical CT scanners. The procedure is efficient in terms of both execution time and memory usage. As results demonstrate, the procedure faithfully follows human-defined measurements and provides far more information than can be defined interactively.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shu-Yen Wan, Erik Leo Ritman M.D., and William E. Higgins "Extraction and analysis of large vascular networks in 3D micro-CT images", Proc. SPIE 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images, (20 May 1999); https://doi.org/10.1117/12.349602
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
3D image processing

Image segmentation

Image processing

3D metrology

3D scanning

Image filtering

Liver

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