Image reconstruction algorithm for in-line phase contrast imaging computed tomography with an improved anisotropic diffusion model
Phase contrast imaging (PCI) is a new physical and biochemical technique. Practical biomedical applications combine PCI with computer tomography (CT), Phase contrast CT (PC-CT) can reconstruct 3D images of samples. How to reconstruct high quality image at a low radiation dose level is a hot topic fo...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ji, Dongjiang [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of x-ray science and technology - Duluth, Minn. : Academic Press, 1989, 23(2015), 3, Seite 311 |
|---|---|
| Übergeordnetes Werk: |
volume:23 ; year:2015 ; number:3 ; pages:311 |
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| 520 | |a Phase contrast imaging (PCI) is a new physical and biochemical technique. Practical biomedical applications combine PCI with computer tomography (CT), Phase contrast CT (PC-CT) can reconstruct 3D images of samples. How to reconstruct high quality image at a low radiation dose level is a hot topic for PC-CT. In order to reduce radiation dose, a strategy is to collect incomplete projection data by few-view projection data. This work presents a reconstruction method for incomplete data PC-CT. It is based on an algebraic iteration reconstruction algorithm and combined with an anisotropic diffusion model to reduce aliasing distortions.To validate the availability of this method, the research carried out a computer-simulated and real experimental synchrotron data. The computer-simulated and real data results demonstrate that the presented method can improve the convergence speed of image reconstruction and reduce the aliasing distortions by incomplete projection data for PC-CT. However, there is no proof that this is true for all kinds of structures. | ||
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Phase contrast imaging (PCI) is a new physical and biochemical technique. Practical biomedical applications combine PCI with computer tomography (CT), Phase contrast CT (PC-CT) can reconstruct 3D images of samples. How to reconstruct high quality image at a low radiation dose level is a hot topic for PC-CT. In order to reduce radiation dose, a strategy is to collect incomplete projection data by few-view projection data. This work presents a reconstruction method for incomplete data PC-CT. It is based on an algebraic iteration reconstruction algorithm and combined with an anisotropic diffusion model to reduce aliasing distortions.To validate the availability of this method, the research carried out a computer-simulated and real experimental synchrotron data. The computer-simulated and real data results demonstrate that the presented method can improve the convergence speed of image reconstruction and reduce the aliasing distortions by incomplete projection data for PC-CT. However, there is no proof that this is true for all kinds of structures. |
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Phase contrast imaging (PCI) is a new physical and biochemical technique. Practical biomedical applications combine PCI with computer tomography (CT), Phase contrast CT (PC-CT) can reconstruct 3D images of samples. How to reconstruct high quality image at a low radiation dose level is a hot topic for PC-CT. In order to reduce radiation dose, a strategy is to collect incomplete projection data by few-view projection data. This work presents a reconstruction method for incomplete data PC-CT. It is based on an algebraic iteration reconstruction algorithm and combined with an anisotropic diffusion model to reduce aliasing distortions.To validate the availability of this method, the research carried out a computer-simulated and real experimental synchrotron data. The computer-simulated and real data results demonstrate that the presented method can improve the convergence speed of image reconstruction and reduce the aliasing distortions by incomplete projection data for PC-CT. However, there is no proof that this is true for all kinds of structures. |
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Phase contrast imaging (PCI) is a new physical and biochemical technique. Practical biomedical applications combine PCI with computer tomography (CT), Phase contrast CT (PC-CT) can reconstruct 3D images of samples. How to reconstruct high quality image at a low radiation dose level is a hot topic for PC-CT. In order to reduce radiation dose, a strategy is to collect incomplete projection data by few-view projection data. This work presents a reconstruction method for incomplete data PC-CT. It is based on an algebraic iteration reconstruction algorithm and combined with an anisotropic diffusion model to reduce aliasing distortions.To validate the availability of this method, the research carried out a computer-simulated and real experimental synchrotron data. The computer-simulated and real data results demonstrate that the presented method can improve the convergence speed of image reconstruction and reduce the aliasing distortions by incomplete projection data for PC-CT. However, there is no proof that this is true for all kinds of structures. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1958069973</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230714144019.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160206s2015 xx ||||| 00| ||eng c</controlfield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160617</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1958069973</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1958069973</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)p833-b2bd252d42e93316f09fa781269f95eed2686ff6ecff5d6b236ba5eb1f542ff00</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0169687420150000023000300311imagereconstructionalgorithmforinlinephasecontrast</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ji, Dongjiang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Image reconstruction algorithm for in-line phase contrast imaging computed tomography with an improved anisotropic diffusion model</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Phase contrast imaging (PCI) is a new physical and biochemical technique. Practical biomedical applications combine PCI with computer tomography (CT), Phase contrast CT (PC-CT) can reconstruct 3D images of samples. How to reconstruct high quality image at a low radiation dose level is a hot topic for PC-CT. In order to reduce radiation dose, a strategy is to collect incomplete projection data by few-view projection data. This work presents a reconstruction method for incomplete data PC-CT. It is based on an algebraic iteration reconstruction algorithm and combined with an anisotropic diffusion model to reduce aliasing distortions.To validate the availability of this method, the research carried out a computer-simulated and real experimental synchrotron data. The computer-simulated and real data results demonstrate that the presented method can improve the convergence speed of image reconstruction and reduce the aliasing distortions by incomplete projection data for PC-CT. However, there is no proof that this is true for all kinds of structures.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hu, Chunhong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Hao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of x-ray science and technology</subfield><subfield code="d">Duluth, Minn. : Academic Press, 1989</subfield><subfield code="g">23(2015), 3, Seite 311</subfield><subfield code="w">(DE-627)182387127</subfield><subfield code="w">(DE-600)1203221-9</subfield><subfield code="w">(DE-576)09450377X</subfield><subfield code="x">0895-3996</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:23</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:3</subfield><subfield code="g">pages:311</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://www.ncbi.nlm.nih.gov/pubmed/26410465</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-DE-84</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">23</subfield><subfield code="j">2015</subfield><subfield code="e">3</subfield><subfield code="h">311</subfield></datafield></record></collection>
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