Evaluation of the OSC‐TV iterative reconstruction algorithm for cone‐beam optical CT
Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone‐beam optical computed tomography (optical CT). One of the uses of optical CT is gel‐based 3D dos...
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| Vydáno v: | Medical physics (Lancaster) Ročník 42; číslo 11; s. 6376 - 6386 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
American Association of Physicists in Medicine
01.11.2015
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| ISSN: | 0094-2405, 2473-4209, 2473-4209 |
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| Abstract | Purpose:
The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone‐beam optical computed tomography (optical CT). One of the uses of optical CT is gel‐based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model‐based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry.
Methods:
This algorithm was evaluated using experimental data acquired by a cone‐beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC‐TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC‐TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied.
Results:
The cone‐beam optical CT data reconstructions showed that OSC‐TV outperforms filtered backprojection in terms of image quality, thanks to a model‐based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated.
Conclusions:
The use of iterative reconstruction improves cone‐beam optical CT image quality in many ways. The comparisons between OSC‐TV and filtered backprojection presented in this paper demonstrate that OSC‐TV can potentially improve the rendering of spatial features and reduce cone‐beam optical CT artifacts. |
|---|---|
| AbstractList | Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts. The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts. Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone‐beam optical computed tomography (optical CT). One of the uses of optical CT is gel‐based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model‐based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone‐beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC‐TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC‐TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone‐beam optical CT data reconstructions showed that OSC‐TV outperforms filtered backprojection in terms of image quality, thanks to a model‐based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone‐beam optical CT image quality in many ways. The comparisons between OSC‐TV and filtered backprojection presented in this paper demonstrate that OSC‐TV can potentially improve the rendering of spatial features and reduce cone‐beam optical CT artifacts. The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry.PURPOSEThe present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry.This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied.METHODSThis algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied.The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated.RESULTSThe cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated.The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.CONCLUSIONSThe use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts. |
| Author | Matenine, Dmitri Mascolo‐Fortin, Julia Després, Philippe Goussard, Yves |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26520729$$D View this record in MEDLINE/PubMed https://www.osti.gov/biblio/22482385$$D View this record in Osti.gov |
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Technol. – ident: e_1_2_7_7_1 doi: 10.1088/1742‐6596/3/1/010 – ident: e_1_2_7_15_1 doi: 10.1088/0031‐9155/57/3/665 – ident: e_1_2_7_13_1 doi: 10.1364/JOSAA.1.000612 – ident: e_1_2_7_32_1 doi: 10.1088/1742‐6596/573/1/012076 – volume: 8 start-page: 306 year: 1984 ident: e_1_2_7_20_1 article-title: EM reconstruction algorithms for emission and transmission tomography publication-title: J. Comput. Assisted Tomogr. – ident: e_1_2_7_4_1 doi: 10.1088/0026‐1394/49/5/S231 – ident: e_1_2_7_28_1 doi: 10.1088/0031‐9155/56/5/003 – ident: e_1_2_7_2_1 doi: 10.1118/1.1559835 – volume-title: General Chemistry year: 2010 ident: e_1_2_7_30_1 – ident: e_1_2_7_21_1 doi: 10.1117/12.23640 – ident: e_1_2_7_29_1 doi: 10.1118/1.595328 – ident: e_1_2_7_33_1 doi: 10.1118/1.599009 – ident: e_1_2_7_26_1 – ident: e_1_2_7_16_1 doi: 10.1088/0266‐5611/25/12/123009 – ident: e_1_2_7_11_1 doi: 10.1088/0031‐9155/55/10/003 – ident: e_1_2_7_18_1 doi: 10.1118/1.4914143 – ident: e_1_2_7_31_1 |
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The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total... The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation... Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total... |
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| SubjectTerms | 60 APPLIED LIFE SCIENCES ACCURACY ALGORITHMS ATTENUATION BEAMS Biological material, e.g. blood, urine; Haemocytometers biomedical optical imaging Computed tomography Computerised tomographs computerised tomography COMPUTERIZED SIMULATION COMPUTERIZED TOMOGRAPHY Cone beam computed tomography Cone-Beam Computed Tomography - instrumentation Cone-Beam Computed Tomography - methods cone‐beam reconstruction Digital computing or data processing equipment or methods, specially adapted for specific applications DOSIMETRY GELS Image data processing or generation, in general image denoising Image enhancement or restoration, e.g. from bit‐mapped to bit‐mapped creating a similar image image reconstruction Imaging, Three-Dimensional - methods ITERATIVE METHODS iterative reconstruction medical image processing Medical image quality Medical image reconstruction Modulation transfer functions optical CT PHANTOMS Phantoms, Imaging RADIATION DOSE DISTRIBUTIONS Radiographic Image Enhancement - methods Radiographic Image Interpretation, Computer-Assisted - methods Radiometry - methods RADIOTHERAPY Reproducibility of Results Sensitivity and Specificity SPATIAL RESOLUTION Tomography, Optical - instrumentation Tomography, Optical - methods total variation minimization TRANSFER FUNCTIONS Visual imaging |
| Title | Evaluation of the OSC‐TV iterative reconstruction algorithm for cone‐beam optical CT |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1118%2F1.4931604 https://www.ncbi.nlm.nih.gov/pubmed/26520729 https://www.proquest.com/docview/1729348815 https://www.osti.gov/biblio/22482385 |
| Volume | 42 |
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