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Iterative reconstruction using a Monte Carlo based system transfer matrix for dedicated breast positron emission tomography.

Authors
  • Saha, Krishnendu1
  • Straus, Kenneth J2
  • Chen, Yu3
  • Glick, Stephen J2
  • 1 Ohio Medical Physics Consulting , Dublin, Ohio 43017, USA.
  • 2 Department of Radiology, University of Massachusetts Medical School , Worcester, Massachusetts 01655, USA.
  • 3 Department of Radiation Oncology, Columbia University , New York, New York 10032, USA.
Type
Published Article
Journal
Journal of Applied Physics
Publisher
AIP Publishing
Publication Date
Aug 28, 2014
Volume
116
Issue
8
Pages
84903–84903
Identifiers
PMID: 25371555
Source
Medline
Language
English
License
Unknown

Abstract

To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.

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