title: A generalized reconstruction framework for unconventional PET systems.
abstract: OBJECTIVE
  Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels.
  
  
  METHODS
  The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation-maximization. System geometry can be specified using a simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddon's algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features.
  
  
  RESULTS
  Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries.
  
  
  CONCLUSIONS
  This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations.
authors.affiliation: Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.
authors.forename: Aswin John
authors.initials: AJ
authors.lastname: Mathews
authors.affiliation: Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.
authors.forename: Ke
authors.initials: K
authors.lastname: Li
authors.affiliation: Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110.
authors.forename: Sergey
authors.initials: S
authors.lastname: Komarov
authors.affiliation: Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110.
authors.forename: Bosky
authors.initials: B
authors.lastname: Ravindranath
authors.affiliation: Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: O'Sullivan
authors.affiliation: Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110.
authors.forename: Yuan-Chuan
authors.initials: YC
authors.lastname: Tai
mesh_terms: D000465:Algorithms; D004867:Equipment Design; D016013:Likelihood Functions; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000295:instrumentation* / Q000379:methods*