Fast Correction of Analytical Reconstructions in Sparse View X-ray Computed Tomography; Progress In Electromagnetics Research Symposium - Spring (PIERS)
| Parent link: | Progress In Electromagnetics Research Symposium - Spring (PIERS).— 2017.— [P. 1101-1108] |
|---|---|
| Autor principal: | |
| Autor corporatiu: | |
| Altres autors: | , |
| Sumari: | Title screen With the availability of more powerful computers, iterative reconstruction algorithms are the subject of an ongoing work in the design of more efficient reconstruction algorithms for X-ray computed tomography. In this work, we show how two analytical reconstruction algorithms can be improved by correcting the corresponding reconstructions using a randomized iterative reconstruction algorithm. The combined analytical reconstruction followed by randomized iterative reconstruction can also be viewed as a reconstruction algorithm which, in the experiments we have conducted, uses up to 35% less projection angles as compared to the analytical reconstruction algorithms and produces the same results in terms of quality of reconstruction, without increasing the execution time significantly. Режим доступа: по договору с организацией-держателем ресурса |
| Idioma: | anglès |
| Publicat: |
2017
|
| Matèries: | |
| Accés en línia: | https://doi.org/10.1109/PIERS.2017.8261911 |
| Format: | Electrònic Capítol de llibre |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=664822 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 664822 | ||
| 005 | 20250815092805.0 | ||
| 035 | |a (RuTPU)RU\TPU\network\36007 | ||
| 035 | |a RU\TPU\network\28212 | ||
| 090 | |a 664822 | ||
| 100 | |a 20210520d2017 k||y0engy50 ba | ||
| 101 | 0 | |a eng | |
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i | |
| 182 | 0 | |a b | |
| 200 | 1 | |a Fast Correction of Analytical Reconstructions in Sparse View X-ray Computed Tomography |f D. Trinca, Zhong Yang, J. Royuela-del-Val | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 7 tit.] | ||
| 330 | |a With the availability of more powerful computers, iterative reconstruction algorithms are the subject of an ongoing work in the design of more efficient reconstruction algorithms for X-ray computed tomography. In this work, we show how two analytical reconstruction algorithms can be improved by correcting the corresponding reconstructions using a randomized iterative reconstruction algorithm. The combined analytical reconstruction followed by randomized iterative reconstruction can also be viewed as a reconstruction algorithm which, in the experiments we have conducted, uses up to 35% less projection angles as compared to the analytical reconstruction algorithms and produces the same results in terms of quality of reconstruction, without increasing the execution time significantly. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 463 | |t Progress In Electromagnetics Research Symposium - Spring (PIERS) |o the 38th proceedings, St. Petersburg, Russia, 22-25 May, 2017 |v [P. 1101-1108] |d 2017 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a reconstruction algorithms | |
| 610 | 1 | |a iterative algorithms | |
| 610 | 1 | |a detectors | |
| 610 | 1 | |a computed tomography | |
| 610 | 1 | |a image reconstruction | |
| 610 | 1 | |a electromagnetics | |
| 610 | 1 | |a springs | |
| 610 | 1 | |a алгоритмы | |
| 610 | 1 | |a детекторы | |
| 610 | 1 | |a компьютерная томография | |
| 610 | 1 | |a изображения | |
| 610 | 1 | |a электромагнетизм | |
| 700 | 1 | |a Trinca |b D. | |
| 701 | 0 | |a Zhong Yang |c specialist in the field of lightning engineering |c Associate Professor of Tomsk Polytechnic University, Ph.D |f 1990- |3 (RuTPU)RU\TPU\pers\39798 | |
| 701 | 1 | |a Royuela-del-Val |b J. |g Javier | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа новых производственных технологий |b Отделение материаловедения |3 (RuTPU)RU\TPU\col\23508 |
| 801 | 2 | |a RU |b 63413507 |c 20210520 |g RCR | |
| 856 | 4 | |u https://doi.org/10.1109/PIERS.2017.8261911 | |
| 942 | |c CF | ||