Image deconvolution in digital autoradiography: A preliminary study

Mutian Zhang, Qing Chen, Xiao Feng Li, Joseph O'Donoghue, Shutian Ruan, Pat Zanzonico, C. Clifton Ling, John L. Humm

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)522-530
Number of pages9
JournalMedical physics
Issue number2
StatePublished - 2008


  • Digital autoradiography
  • Image deconvolution
  • Imaging plate
  • Point spread function
  • Richardson-Lucy algorithm

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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