The derivation and verification of a non-stationary, optimal smoothing filter for nuclear medicine image data

D. M. Hull, C. S. Peskin, A. M. Rabinowitz, J. P. Wexler, M. D. Blaufox

Research output: Contribution to journalArticle

Abstract

A non-stationary smoothing filter for digital medicine image data, degraded by Poisson noise, has been derived and applied to temporal simulated and clinical gated blood pool study (GBPS) data. The derived filter is automatically calculated from a large group (library) of similar GBPS which are representative of all studies acquired according to the same protocol in a defined patient population (the ensemble). The filter is designed to minimize the mean-square difference between the filtered data and the true image values; it provides an optimal trade-off between noise reduction and signal degradation for members of the ensemble. The filter is evaluated using a computer simulated ensemble of GBPS. Libraries of Poisson-degraded and non-degraded studies were generated. Libraries of up to 400 Poisson-degraded simulated studies were used to estimate optimal temporal filters that, when applied to Poisson-degraded members of the ensemble not included in the libraries, reduced the mean-square error in the raw data by 65%.

Original languageEnglish (US)
Article number005
Pages (from-to)1641-1662
Number of pages22
JournalPhysics in Medicine and Biology
Volume35
Issue number12
DOIs
StatePublished - Dec 1 1990

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ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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