Automated motion correction for in vivo optical projection tomography / Shouping Zhu, Di Dong, Udo Jochen Birk, Matthias Rieckher, Nektarios Tavernarakis, Xiaochao Qu, Member, IEEE, Jimin Liang, Member, IEEE, Jie Tian, Fellow IEEE, and Jorge Ripoll
In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation. We decompose object movement into translation and rotation, and discuss how to correct for both translation and general motion simultaneously. Since finding the center of rotation accurately is critical in OPT, we also point out that the system's geometrical offset can be considered as object translation and therefore also calibrated through the translation estimation method. In order to verify the algorithm effectiveness, both simulated and in vivo OPT experiments are performed. Our results demonstrate that the proposed approach is capable of decreasing movement artifacts significantly thus providing high quality reconstructed images in the presence of object motion..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
24 February 2012 2012 |
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| Erschienen: |
24 February 2012 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:31 |
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| Enthalten in: |
IEEE transactions on medical imaging - 31(2012), 7, Seite 1358-1371 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zhu, Shouping [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Gesehen am 14.08.2018 |
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| Umfang: |
14 |
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| doi: |
10.1109/TMI.2012.2188836 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
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| 245 | 1 | 0 | |a Automated motion correction for in vivo optical projection tomography |c Shouping Zhu, Di Dong, Udo Jochen Birk, Matthias Rieckher, Nektarios Tavernarakis, Xiaochao Qu, Member, IEEE, Jimin Liang, Member, IEEE, Jie Tian, Fellow IEEE, and Jorge Ripoll |
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| 520 | |a In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation. We decompose object movement into translation and rotation, and discuss how to correct for both translation and general motion simultaneously. Since finding the center of rotation accurately is critical in OPT, we also point out that the system's geometrical offset can be considered as object translation and therefore also calibrated through the translation estimation method. In order to verify the algorithm effectiveness, both simulated and in vivo OPT experiments are performed. Our results demonstrate that the proposed approach is capable of decreasing movement artifacts significantly thus providing high quality reconstructed images in the presence of object motion. | ||
| 650 | 4 | |a Image reconstruction | |
| 650 | 4 | |a Animals | |
| 650 | 4 | |a Algorithms | |
| 650 | 4 | |a Artifacts | |
| 650 | 4 | |a automated motion correction | |
| 650 | 4 | |a Caenorhabditis elegans | |
| 650 | 4 | |a calibration | |
| 650 | 4 | |a Calibration | |
| 650 | 4 | |a Computer Simulation | |
| 650 | 4 | |a Equations | |
| 650 | 4 | |a Estimation | |
| 650 | 4 | |a Geometry | |
| 650 | 4 | |a Helgason-Ludwig consistency condition | |
| 650 | 4 | |a Helgason-Ludwig consistency condition (HLCC) | |
| 650 | 4 | |a high quality reconstructed image | |
| 650 | 4 | |a Image Processing, Computer-Assisted | |
| 650 | 4 | |a Imaging | |
| 650 | 4 | |a in-vivo OPT | |
| 650 | 4 | |a in-vivo optical projection tomography | |
| 650 | 4 | |a motion correction | |
| 650 | 4 | |a Motion estimation | |
| 650 | 4 | |a Movement | |
| 650 | 4 | |a movement artifacts | |
| 650 | 4 | |a object motion estimation | |
| 650 | 4 | |a object movement | |
| 650 | 4 | |a object translation | |
| 650 | 4 | |a optical projection tomography (OPT) | |
| 650 | 4 | |a Optimized production technology | |
| 650 | 4 | |a parallel beam illumination | |
| 650 | 4 | |a Phantoms, Imaging | |
| 650 | 4 | |a projection data | |
| 650 | 4 | |a reconstructed image quality | |
| 650 | 4 | |a reconstructed image resolution | |
| 650 | 4 | |a system geometrical offset | |
| 650 | 4 | |a Tomography, Optical | |
| 650 | 4 | |a translation estimation method | |
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