Image deconvolution in digital autoradiography: a preliminary study. Academic Article uri icon

Overview

abstract

  • Digital autoradiography (DAR) is a powerful method to determine quantitatively the "small-scale" (i.e., submillimeter) distribution of a radiotracer within a tissue section. However, the limited spatial resolution of the DAR image, due to blurring by the point spread function (PSF), can result in a poor correlation with tissue histology and immunohistochemistry. The authors attempt to overcome this limitation by recovering the radiotracer distribution by image deconvolution using the Richardson-Lucy algorithm and a measured PSF obtained from a small radioactive source on hydrophobic microscope slide. Simulation studies have shown that the deconvolution algorithm reliably recovers the pixel values corresponding to the radioactivity distributions. As an example, the proposed image restoration approach has been tested with DAR images of different radiolabeled markers on tumor sections obtained from clinical and preclinical animal model studies. Digital autoradiograms following deconvolution show improved sharpness and contrast relative to the unprocessed autoradiograms.

publication date

  • February 1, 2008

Research

keywords

  • Algorithms
  • Artifacts
  • Autoradiography
  • Image Enhancement
  • Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Signal Processing, Computer-Assisted

Identity

PubMed Central ID

  • PMC2668928

Scopus Document Identifier

  • 38849127416

Digital Object Identifier (DOI)

  • 10.1118/1.2828198

PubMed ID

  • 18383673

Additional Document Info

volume

  • 35

issue

  • 2