Reconstruction of Tomographic Images from Sparse Data Sets By a New Finite Element Maximum Entropy Approach.

Abstract

A new algorithm for the reconstruction of tomographic images from parse data sets is presented. A finite element technique was devised to solve the constrained optimization problem which resulted from the analysis using the maximum entropy formalism. The improvement in reconstruction image quality over conventional techniques is illustrated by several examples. Keywords: Computed Tomography, Reconstruction, Image Analysis, Finite Element Method, Sparse Data Analysis, Image Reconstruction, Finite Element Method.

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Document Details

Document Type
Technical Report
Publication Date
Apr 07, 1987
Accession Number
ADA183639

Entities

People

  • Csaba K. Zoltani
  • G. J. Klem
  • R. T. Smith

Organizations

  • Ballistic Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Ammunition
  • Computer Programs
  • Data Sets
  • Detectors
  • Engineering
  • Finite Element Analysis
  • Geometry
  • Jet Propulsion
  • Mathematics
  • Mechanical Engineering
  • Military Research
  • Munitions
  • Optimization
  • Three Dimensional
  • X Rays
  • X-Ray Computed Tomography

Fields of Study

  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Mathematical Modeling and Probability Theory.
  • Operations Research