A Fuzzy Clustering-Based X-Ray Computed Tomography Simulation under Incomplete Measurements

Shi Hong Yue; Xiu Juan Bao; Jin Xin Zhang

doi:10.4028/www.scientific.net/AMR.748.651

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 748A Fuzzy Clustering-Based X-Ray Computed Tomography...

A Fuzzy Clustering-Based X-Ray Computed Tomography Simulation under Incomplete Measurements

Abstract:

The existing x-ray computed tomography algorithm simulation assume the complete measurements of the investigated objectives to be available, but this is not true in most applications. To overcome the problem, we creatively propose a method of image reconstruction based on fuzzy clustering algorithm under limited measurements. Different from the existing algorithms, we map all measurements into a set of vectors and cluster all vectors for the image reconstruction. The proposed algorithm aims to be easily realized, lower time complexity, and applicable in a real-time manner in case of limited measurements of the investigated objectives. Experiments demonstrate the effectiveness and efficiency of the proposed algorithm.

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Periodical:

Advanced Materials Research (Volume 748)

Pages:

651-654

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.748.651

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Online since:

August 2013

Authors:

Shi Hong Yue, Xiu Juan Bao, Jin Xin Zhang

Keywords:

Fuzzy Clustering, Multiphase Flow Measurement, X-Ray Computed Tomography

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