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Segment self-guide reconstruction algorithm based on object-oriented quantization

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Aiming at the problem of inaccurate imaging model of three-dimensional (3D) reconstruction of rotational DSA (digital subtraction angiography) images, firstly a nonlinear model based on object-oriented quantization is introduced. The model quantizes the projective pixel of 3D vessel slice as the vessel number that the X-ray goes through. Then, under the constraint of limited views and sparse projections, a slice reconstruction algorithm named segment self-guide reconstruction (SSGR) is developed. It converts the slice reconstruction of N+1 level nonlinear quantized DSA image to the reconstruction of N vessel cross-sections. The SSGR is especially suitable for solving the problem of sparse projections and limited-views. Finally, the simulated results have proved the feasibility of the model and the validity of the algorithm.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter M. A. Sloot, David Abramson, Alexander V. Bogdanov, Yuriy E. Gorbachev, Jack J. Dongarra, Albert Y. Zomaya
PublisherSpringer Verlag
Pages457-465
Number of pages9
ISBN (Print)9783540448600
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2657
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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