Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data

WANG Zhen-Tian; HUANG Zhi-Feng; ZHANG Li; KANG Ke-Jun; CHEN Zhi-Qiang; ZHU Pei-Ping

doi:10.1088/1674-1137/33/11/010

Chinese Physics C> 2009, Vol. 33> Issue(11) : 981-985 DOI: 10.1088/1674-1137/33/11/010

Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data

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Abstract：
Tomosynthesis is a three-dimension reconstruction method that can remove the effect of superimposition with limited angle projections. It is especially promising in mammography where radiation dose is concerned. In this paper, we propose a maximum likelihood tomosynthesis reconstruction algorithm (ML-TS) on the apparent absorption data of diffraction enhanced imaging (DEI). The motivation of this contribution is to develop a tomosynthesis algorithm in low-dose or noisy circumstances and make DEI get closer to clinic application. The theoretical statistical models of DEI data in physics are analyzed and the proposed algorithm is validated with the experimental data at the Beijing Synchrotron Radiation Facility (BSRF). The results of ML-TS have better contrast compared with the well known `shift-and-add' algorithm and FBP algorithm.

References

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WANG Zhen-Tian, HUANG Zhi-Feng, ZHANG Li, KANG Ke-Jun, CHEN Zhi-Qiang and ZHU Pei-Ping. Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data[J]. Chinese Physics C, 2009, 33(11): 981-985. doi: 10.1088/1674-1137/33/11/010

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Received: 2008-12-17
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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data

Corresponding author: HUANG Zhi-Feng,

Received Date: 2008-12-17

Accepted Date: 2009-04-02

Available Online: 2009-11-05

Abstract:

Tomosynthesis is a three-dimension reconstruction method that can remove the effect of superimposition with limited angle projections. It is especially promising in mammography where radiation dose is concerned. In this paper, we propose a maximum likelihood tomosynthesis reconstruction algorithm (ML-TS) on the apparent absorption data of diffraction enhanced imaging (DEI). The motivation of this contribution is to develop a tomosynthesis algorithm in low-dose or noisy circumstances and make DEI get closer to clinic application. The theoretical statistical models of DEI data in physics are analyzed and the proposed algorithm is validated with the experimental data at the Beijing Synchrotron Radiation Facility (BSRF). The results of ML-TS have better contrast compared with the well known `shift-and-add' algorithm and FBP algorithm.

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Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data

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