| Title |
Advanced virtual monochromatic reconstruction of dual-energy unenhanced brain computed tomography in children: comparison of image quality against standard mono-energetic images and conventional polychromatic computed tomography
|
|---|---|
| Published in |
Pediatric Radiology, June 2017
|
| DOI | 10.1007/s00247-017-3908-8 |
| Pubmed ID | |
| Authors |
Juil Park, Young Hun Choi, Jung-Eun Cheon, Woo Sun Kim, In-One Kim, Seong Yong Pak, Bernhard Krauss |
| Abstract |
Advanced virtual monochromatic reconstruction from dual-energy brain CT has not been evaluated in children. To determine the most effective advanced virtual monochromatic imaging energy level for maximizing pediatric brain parenchymal image quality in dual-energy unenhanced brain CT and to compare this technique with conventional monochromatic reconstruction and polychromatic scanning. Using both conventional (Mono) and advanced monochromatic reconstruction (Mono+) techniques, we retrospectively reconstructed 13 virtual monochromatic imaging energy levels from 40 keV to 100 keV in 5-keV increments from dual-source, dual-energy unenhanced brain CT scans obtained in 23 children. We analyzed gray and white matter noise ratios, signal-to-noise ratios and contrast-to-noise ratio, and posterior fossa artifact. We chose the optimal mono-energetic levels and compared them with conventional CT. For Mono+maximum optima were observed at 60 keV, and minimum posterior fossa artifact at 70 keV. For Mono, optima were at 65-70 keV, with minimum posterior fossa artifact at 75 keV. Mono+ was superior to Mono and to polychromatic CT for image-quality measures. Subjective analysis rated Mono+superior to other image sets. Optimal virtual monochromatic imaging using Mono+ algorithm demonstrated better image quality for gray-white matter differentiation and reduction of the artifact in the posterior fossa. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 18% |
| Student > Ph. D. Student | 2 | 9% |
| Student > Postgraduate | 2 | 9% |
| Student > Master | 2 | 9% |
| Student > Doctoral Student | 1 | 5% |
| Other | 4 | 18% |
| Unknown | 7 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 41% |
| Physics and Astronomy | 2 | 9% |
| Arts and Humanities | 1 | 5% |
| Unspecified | 1 | 5% |
| Unknown | 9 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 September 2017.
All research outputs
#14,356,760
of 22,990,068 outputs
Outputs from Pediatric Radiology
#1,199
of 2,093 outputs
Outputs of similar age
#176,549
of 315,713 outputs
Outputs of similar age from Pediatric Radiology
#33
of 49 outputs
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