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Non Iterative Methods for 3D SPECT Image Reconstruction

Non Iterative Methods for 3D SPECT Image Reconstruction
3D SPECT 图像重建的非迭代方法
批准号:
6512821
负责人:
XIAOCHUAN PAN
金额:
$30.93万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
1996
资助国家:
美国
项目状态:
已结题
起止时间:
1996-04-01 至 2006-03-31

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中文摘要
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英文摘要
DESCRIPTION (Verbatim from Applicant's Abstract): Single-photon emission computed tomography (SPECT) is playing an increasingly important role in modern medicine for imaging the brain, liver, kidneys, prostate, and other organs. The broad objectives of the project are to develop non-iterative methods for accurate and efficient reconstruction of three-dimensional (3D) images in SPECT and to evaluate these methods in clinical applications. Non-iterative methods for image reconstruction in SPECT are inherently computationally efficient. They are attractive in practice because they avoid problems that plague other methods. Most importantly, they can facilitate a closed-form: analysis of image statistics and aliasing, allowing the development of strategies for optimal suppression of the effects of noise, aliasing, and other errors. The research on non-iterative methods will significantly enhance the ability of SPECT to detect subtle lesions and to quantify accurately physiologic parameters in research and clinical applications. This proposal is intended specifically for further development of non-iterative, statistically optimal, computationally efficient, and numerically robust reconstruction methods in 3D SPECT and for evaluation of these methods in clinical SPECT studies such as In-111 Prostascint SPECT imaging of prostate cancer. We expect that the proposed methods will adequately compensate for the effects of photon attenuation, distance dependent spatial resolution, and data noise. We will apply methods developed by other investigators to compensate for scatter. We believe that our research will significantly strengthen the ability of SPECT for detecting subtle lesions in clinical applications. The specific aims of the proposed research are (1) to fur ther develop non-iterative methods for optimal estimation of the ideal sinogram, (2) to develop adaptive and robust filtering approaches, (3) to investigate and mitigate the effects of additional sources of error, (4) to evaluate the proposed methods using phantom studies, and (5) to evaluate the proposed methods in clinical studies.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Sampling and aliasing consequences of quarter-detector offset use in helical CT.
螺旋 CT 中四分之一探测器偏移使用的采样和混叠后果。
DOI: 10.1109/tmi.2004.826950
发表时间: 2004
期刊: IEEE transactions on medical imaging
影响因子: 10.6
作者: [LaRivière,PatrickJ, Pan,Xiaochuan]
通讯作者: Pan,Xiaochuan
Algorithm-Enabled Auto-Calibrating Quantitative Dual-Energy CT
  • 批准号:
    10448987
  • 项目类别:
  • 资助金额:
    $22.83万
  • 财政年份:
    2022
  • 负责人:
    XIAOCHUAN PAN
  • 依托单位:
Advanced iterative image reconstruction for digital breast tomosynthesis - Resubmission 01
  • 批准号:
    9978584
  • 项目类别:
  • 资助金额:
    $52.85万
  • 财政年份:
    2018
  • 负责人:
    XIAOCHUAN PAN
  • 依托单位:
Advanced iterative image reconstruction for digital breast tomosynthesis - Resubmission 01
  • 批准号:
    10224861
  • 项目类别:
  • 资助金额:
    $51.79万
  • 财政年份:
    2018
  • 负责人:
    XIAOCHUAN PAN
  • 依托单位:
36th Annual International Conference of the IEEE Engineering in Medicine and Biol
  • 批准号:
    8720474
  • 项目类别:
  • 资助金额:
    $1.0万
  • 财政年份:
    2014
  • 负责人:
    XIAOCHUAN PAN
  • 依托单位:
海外基金