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Title: Model-based computed tomography for nondestructive evaluation

Technical Report ·
OSTI ID:5806601

X-ray Computer Tomography (CT) has become a routine medical diagnostic for cross-sectional imaging of the body. Yet, even with over two decades of experience in the medical field, CT technology is not routinely used in industrial settings for nondestructive evaluation (NDE). The sparsity of industrial CT systems is due not only to large initial capital costs, but also to several problems of a physical nature and a mathematical nature. In this research, we have taken a fresh look at the industrial CT imaging problem and present several major contributions to the field. Explicit relationships of the underlying mathematics, along with new properties, are summarized. Conventional methods of image reconstruction are then developed, and their strengths and limitations are established for practical industrial CT. New methods for geometry estimation from unreconstructed projection data are developed that are effective for both experimental and simulated data. A major study of image reconstruction from incomplete measurements, a common problem plaguing industrial CT, is presented. First, previously proposed techniques are studied in the context of NDE, then a class of reconstruction methods -- the domain-iterative algorithms, some of which are new -- is developed under a common framework and shown to have an infinite number of hybrid methods. Implementation of domain-iterative methods is limited by computer requirements and by alignment accuracy between the data and models. New techniques for addressing these problems are presented. A fast, parallel technique for computing Radon transform and backprojection operations is described. Software simulations of this technique are tested, while a hardware implementation is on-going in a separate project. Future research areas in industrial CT are summarized. 208 refs., 54 figs., 8 tabs.

Research Organization:
Lawrence Livermore National Lab., CA (USA)
Sponsoring Organization:
USDOE; USDOE, Washington, DC (USA)
DOE Contract Number:
W-7405-ENG-48
OSTI ID:
5806601
Report Number(s):
UCRL-LR-106884; ON: DE91013462
Resource Relation:
Other Information: Thesis (Ph.D.)
Country of Publication:
United States
Language:
English