Heuristic wavelet approach for low-dose EPR tomographic reconstruction: An applicability analysis with phantom and in vivo imaging
Electron paramagnetic resonance imaging (EPRI) is a new functional imaging modality that can provide valuable in vivo physiological information and aids as a complimentary imaging technique to MRI and PET of tissues especially with respect to in vivo pO2, redox status and pharmacology. EPRI deals wi...
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| Vydané v: | Expert systems with applications Ročník 39; číslo 5; s. 5717 - 5726 |
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01.04.2012
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | Electron paramagnetic resonance imaging (EPRI) is a new functional imaging modality that can provide valuable
in vivo physiological information and aids as a complimentary imaging technique to MRI and PET of tissues especially with respect to
in vivo pO2, redox status and pharmacology. EPRI deals with the measurement of distribution and
in vivo dynamics, using exogenous paramagnetic spin probes injected into the scan subject. The bio-clearance and dosage of these spin probes are issues of concern in EPRI. As a consequence, tomographic reconstruction from ‘noisy’ and ‘sparse’ number of projections is highly desirable in EPRI for the purpose of dose reduction and fast acquisition time respectively. The aim of research is to address the incompleteness of such projection data by developing a software which requires no change in acquisition hardware and/or no a priori knowledge of imaging process. The new software approach integrates soft computing and multiresolution within tomographic reconstruction to “intelligently” extract the details of importance at several levels of resolution. The new multiresolution reconstruction algorithm is based on wavelet transform with computational complexity same as the clinically used, filtered backprojection (FBP) method, except that the filters are now angle dependent. Gain in intelligence is achieved employing multiobjective genetic algorithm (GA) to find values for wavelet denoising threshold with optimum performance in terms of signal to noise ratio (SNR) and resolution of the reconstructed image. Feasibility of the approach for fast and low dose tomographic reconstruction is demonstrated with simulated SheppLogan head phantom. Subsequently, the experimental results with phantom and
in vivo EPRI proves that the developed method can reduce the dose level and number of projections by 60–75% in tomographic reconstruction. In particular the quantitative analysis, using RMSE, PSNR and Liu’s error factor, shows that our approach outperforms the widely used, FBP and state-of-art wavelet-based tomographic reconstruction method in achieving image quality with acceptable diagnostic accuracy. |
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| AbstractList | Electron paramagnetic resonance imaging (EPRI) is a new functional imaging modality that can provide valuable
in vivo physiological information and aids as a complimentary imaging technique to MRI and PET of tissues especially with respect to
in vivo pO2, redox status and pharmacology. EPRI deals with the measurement of distribution and
in vivo dynamics, using exogenous paramagnetic spin probes injected into the scan subject. The bio-clearance and dosage of these spin probes are issues of concern in EPRI. As a consequence, tomographic reconstruction from ‘noisy’ and ‘sparse’ number of projections is highly desirable in EPRI for the purpose of dose reduction and fast acquisition time respectively. The aim of research is to address the incompleteness of such projection data by developing a software which requires no change in acquisition hardware and/or no a priori knowledge of imaging process. The new software approach integrates soft computing and multiresolution within tomographic reconstruction to “intelligently” extract the details of importance at several levels of resolution. The new multiresolution reconstruction algorithm is based on wavelet transform with computational complexity same as the clinically used, filtered backprojection (FBP) method, except that the filters are now angle dependent. Gain in intelligence is achieved employing multiobjective genetic algorithm (GA) to find values for wavelet denoising threshold with optimum performance in terms of signal to noise ratio (SNR) and resolution of the reconstructed image. Feasibility of the approach for fast and low dose tomographic reconstruction is demonstrated with simulated SheppLogan head phantom. Subsequently, the experimental results with phantom and
in vivo EPRI proves that the developed method can reduce the dose level and number of projections by 60–75% in tomographic reconstruction. In particular the quantitative analysis, using RMSE, PSNR and Liu’s error factor, shows that our approach outperforms the widely used, FBP and state-of-art wavelet-based tomographic reconstruction method in achieving image quality with acceptable diagnostic accuracy. |
| Author | Murugesan, R. Thavavel, V. Krishna, M.C. Jaffer Basha, J. |
| Author_xml | – sequence: 1 givenname: V. surname: Thavavel fullname: Thavavel, V. email: thavavelmurugesanv@gmail.com organization: Department of Computer Applications, Karunya University, Coimbatore, Tamilnadu, India – sequence: 2 givenname: J. surname: Jaffer Basha fullname: Jaffer Basha, J. email: jafferbasha@gmail.com organization: Department of Computer Science and Engineering, Sree Sowdambika College of Engineering, Aruppukottai, Tamilnadu, India – sequence: 3 givenname: M.C. surname: Krishna fullname: Krishna, M.C. organization: Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, USA – sequence: 4 givenname: R. surname: Murugesan fullname: Murugesan, R. email: rammku@eth.net organization: Networking Resource Center in Biological Sciences, Madurai Kamaraj University, Madurai, Tamilnadu, India |
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| Cites_doi | 10.1109/42.363108 10.2307/1390677 10.1049/ip-vis:19960513 10.1016/j.ces.2007.04.026 10.1109/42.481444 10.1109/97.720556 10.1109/83.892445 10.1109/TMI.2008.923698 10.1006/jmre.2001.2487 10.1109/83.388081 10.1063/1.1318917 10.1109/83.624961 10.1109/TMI.2008.923983 10.1016/j.compbiomed.2007.01.010 10.1109/TMI.2005.862206 10.1023/A:1022978322046 10.1007/s10851-007-0056-z 10.1016/j.eswa.2010.10.037 10.1002/nbm.897 10.1016/j.compmedimag.2006.12.003 10.1016/j.eswa.2008.08.065 10.1109/TMI.1982.4307558 10.1016/j.ijrobp.2010.07.1486 |
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| Keywords | Genetic algorithm and Multiobjective function Filtered backprojection Low-dose tomographic reconstruction Wavelet thresholding Threshold optimization Electron magnetic resonance imaging |
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| SubjectTerms | Electron magnetic resonance imaging Filtered backprojection Genetic algorithm and Multiobjective function Low-dose tomographic reconstruction Threshold optimization Wavelet thresholding |
| Title | Heuristic wavelet approach for low-dose EPR tomographic reconstruction: An applicability analysis with phantom and in vivo imaging |
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