A focus-of-attention preprocessing scheme for em-ml pet reconstruction

Jens Gregor, Dean A. Huff

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

The expectation-maximization maximum-likelihood (EMML) algorithm belongs to a family of algorithms that compute positron emission tomography (PET) reconstructions by iteratively solving a large linear system of equations. We describe a preprocessing scheme for automatically focusing the attention and thus the computational resources on a subset of the equations and unknowns. Experimental work with a CM-5 parallel computer implementation using a simulated phantom as well as real data obtained from an ECAT 921 PET scanner indicates that quite significant savings can be obtained with respect to both time and space requirements of the EM-ML algorithm without compromising the quality of the reconstructed images.

Original languageEnglish (US)
Pages (from-to)218-223
Number of pages6
JournalIEEE Transactions on Medical Imaging
Volume16
Issue number2
DOIs
StatePublished - Jan 1 1997
Externally publishedYes

Fingerprint

Pets
Positron emission tomography
Positron-Emission Tomography
Maximum likelihood
Linear systems

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

A focus-of-attention preprocessing scheme for em-ml pet reconstruction. / Gregor, Jens; Huff, Dean A.

In: IEEE Transactions on Medical Imaging, Vol. 16, No. 2, 01.01.1997, p. 218-223.

Research output: Contribution to journalArticle

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