Image reconstruction from sparse data in synchrotron-radiation-based microtomography

Abstract

Synchrotron-radiation-based microcomputed-tomography (SR- CT) is a powerful tool for yielding 3D structural information of high spatial and contrast resolution about a specimen preserved in its natural state. A large number of projection views are required currently for yielding SR- CT images by use of existing algorithms without significant artifacts. When a wet biological specimen is imaged, synchrotron x-ray radiation from a large number of projection views can result in significant structural deformation within the specimen. A possible approach to reducing imaging time and specimen deformation is to decrease the number of projection views. In the work, using reconstruction algorithms developed recently for medical computed tomography (CT), we investigate and demonstrate image reconstruction from sparse-view data acquired in SR- CT. Numerical results of our study suggest that images of practical value can be obtained from data acquired at a number of projection views significantly lower than those used currently in a typical SR- CT imaging experiment.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 18, 2011
Accession Number
ADA590173

Entities

People

  • D. Xia
  • E. Y. Sidky
  • F. De Carlo
  • Jia Bian
  • X. Pan
  • Xian Xiao
  • Xingyue Han

Organizations

  • Argonne National Laboratory

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Coordinate Systems
  • Data Acquisition
  • Detectors
  • Diagnostic Imaging
  • Energy Bands
  • Engineering
  • Image Processing
  • Image Reconstruction
  • Images
  • Optical Images
  • Radiation
  • Synchrotron Radiation
  • Synchrotrons
  • Tomography
  • X Rays
  • X-Ray Computed Tomography

Fields of Study

  • Physics

Readers

  • Ballistic Missile Meteorology
  • Image Processing and Computer Vision.
  • Medical Imaging.