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Title: A reconstruction algorithms for helical cone-beam SPECT

Abstract

Cone-beam SPECT provides improved sensitivity for imaging small organs like the brain and heart. However, current cone-beam tomography with the focal point traversing a planar orbit does not acquire sufficient data to give an accurate reconstruction. In this paper, the authors employ a data-acquisition method which obtains complete data for cone-beam SPECT by simultaneously rotating the gamma camera and translating the patient bed, so that cone-beam projections can be obtained with the focal point traversing a helix surrounding the patient. An implementation of Grangeat's algorithm for helical cone-beam projections is developed. The algorithm requires a rebinning step to convert cone-beam data to parallel-beam data which are then reconstructed using the 3D Radon inversion. A fast new rebinning scheme is developed which uses all of the detected data to reconstruct the image and properly normalizes any multiply scanned data. This algorithm is shown to produce less artifacts than the commonly used Feldkamp algorithm when applied to either a circular planar orbit or a helical orbit acquisition. The algorithm can easily be extended to any arbitrary orbit.

Authors:
; ;  [1]
  1. Univ. of Utah, Salt Lake City, UT (United States). Dept. of Radiology
Publication Date:
OSTI Identifier:
6057740
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Nuclear Science (Institute of Electrical and Electronics Engineers); (United States)
Additional Journal Information:
Journal Volume: 40:4 part 1; Journal ID: ISSN 0018-9499
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY; ALGORITHMS; ACCURACY; DATA ACQUISITION; IMAGE PROCESSING; OPTIMIZATION; COMPUTERIZED TOMOGRAPHY; DIAGNOSTIC TECHNIQUES; EMISSION COMPUTED TOMOGRAPHY; MATHEMATICAL LOGIC; PROCESSING; TOMOGRAPHY; 550601* - Medicine- Unsealed Radionuclides in Diagnostics

Citation Formats

Weng, Y, Zeng, G L, and Gullberg, G T. A reconstruction algorithms for helical cone-beam SPECT. United States: N. p., 1993. Web. doi:10.1109/23.256718.
Weng, Y, Zeng, G L, & Gullberg, G T. A reconstruction algorithms for helical cone-beam SPECT. United States. https://doi.org/10.1109/23.256718
Weng, Y, Zeng, G L, and Gullberg, G T. Sun . "A reconstruction algorithms for helical cone-beam SPECT". United States. https://doi.org/10.1109/23.256718.
@article{osti_6057740,
title = {A reconstruction algorithms for helical cone-beam SPECT},
author = {Weng, Y and Zeng, G L and Gullberg, G T},
abstractNote = {Cone-beam SPECT provides improved sensitivity for imaging small organs like the brain and heart. However, current cone-beam tomography with the focal point traversing a planar orbit does not acquire sufficient data to give an accurate reconstruction. In this paper, the authors employ a data-acquisition method which obtains complete data for cone-beam SPECT by simultaneously rotating the gamma camera and translating the patient bed, so that cone-beam projections can be obtained with the focal point traversing a helix surrounding the patient. An implementation of Grangeat's algorithm for helical cone-beam projections is developed. The algorithm requires a rebinning step to convert cone-beam data to parallel-beam data which are then reconstructed using the 3D Radon inversion. A fast new rebinning scheme is developed which uses all of the detected data to reconstruct the image and properly normalizes any multiply scanned data. This algorithm is shown to produce less artifacts than the commonly used Feldkamp algorithm when applied to either a circular planar orbit or a helical orbit acquisition. The algorithm can easily be extended to any arbitrary orbit.},
doi = {10.1109/23.256718},
url = {https://www.osti.gov/biblio/6057740}, journal = {IEEE Transactions on Nuclear Science (Institute of Electrical and Electronics Engineers); (United States)},
issn = {0018-9499},
number = ,
volume = 40:4 part 1,
place = {United States},
year = {1993},
month = {8}
}