A study on noise reduction for dual-energy CT material decomposition with autoencoder
Purpose A major challenge for the material decomposition task of the dual-energy computed tomography (DECT) is the algorithm often suffers from heavy noise in the results. The purpose of this study is to propose a scheme to increase the noise performance of material decomposition. Methods The scheme...
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| Vydáno v: | Radiation detection technology and methods Ročník 3; číslo 3 |
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| Hlavní autoři: | , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Singapore
Springer Singapore
01.09.2019
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| ISSN: | 2509-9930, 2509-9949 |
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| Abstract | Purpose
A major challenge for the material decomposition task of the dual-energy computed tomography (DECT) is the algorithm often suffers from heavy noise in the results. The purpose of this study is to propose a scheme to increase the noise performance of material decomposition.
Methods
The scheme we propose in this paper is to apply an autoencoder-based denoising procedure to the photon-counting DECT images before they are fed into the material decomposition algorithm. We implement the autoencoder (AE) by stacking a series of convolutional and deconvolutional layers. The decomposition technique adopted in our work is an iterative method using least squares estimation with the Huber loss function. The noises of the input and the output of material decomposition are analyzed with both simulated data and real data. Phantom and chicken wing experiments are conducted with a photon-counting-based spectral CT scanner to evaluate the proposed material decomposition scheme.
Results
The noise analysis of the input and the output of material decomposition demonstrates a positive correlation between them. Comparative experiment indicates a noise reduction in the output density maps for 26.07% to 35.65% after the autoencoder pre-processing is applied. The resultant contrast-to-noise ratio is largely increased, correspondingly.
Conclusions
By utilizing the additional autoencoder denoising step, the material decomposition algorithm achieves an improvement in the noise performance of the resultant density maps. |
|---|---|
| AbstractList | Purpose
A major challenge for the material decomposition task of the dual-energy computed tomography (DECT) is the algorithm often suffers from heavy noise in the results. The purpose of this study is to propose a scheme to increase the noise performance of material decomposition.
Methods
The scheme we propose in this paper is to apply an autoencoder-based denoising procedure to the photon-counting DECT images before they are fed into the material decomposition algorithm. We implement the autoencoder (AE) by stacking a series of convolutional and deconvolutional layers. The decomposition technique adopted in our work is an iterative method using least squares estimation with the Huber loss function. The noises of the input and the output of material decomposition are analyzed with both simulated data and real data. Phantom and chicken wing experiments are conducted with a photon-counting-based spectral CT scanner to evaluate the proposed material decomposition scheme.
Results
The noise analysis of the input and the output of material decomposition demonstrates a positive correlation between them. Comparative experiment indicates a noise reduction in the output density maps for 26.07% to 35.65% after the autoencoder pre-processing is applied. The resultant contrast-to-noise ratio is largely increased, correspondingly.
Conclusions
By utilizing the additional autoencoder denoising step, the material decomposition algorithm achieves an improvement in the noise performance of the resultant density maps. |
| ArticleNumber | 44 |
| Author | Wang, Zhe Liu, Shuangquan Li, Mohan Liu, Baodong Wei, Long Xu, Qiong Wei, Cunfeng Zhang, Zhidu Cheng, Zhiwei |
| Author_xml | – sequence: 1 givenname: Mohan surname: Li fullname: Li, Mohan organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 2 givenname: Zhe surname: Wang fullname: Wang, Zhe organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 3 givenname: Qiong surname: Xu fullname: Xu, Qiong organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 4 givenname: Zhidu surname: Zhang fullname: Zhang, Zhidu organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 5 givenname: Zhiwei surname: Cheng fullname: Cheng, Zhiwei organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 6 givenname: Shuangquan surname: Liu fullname: Liu, Shuangquan organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 7 givenname: Baodong surname: Liu fullname: Liu, Baodong organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 8 givenname: Cunfeng surname: Wei fullname: Wei, Cunfeng email: weicf@ihep.ac.cn organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences – sequence: 9 givenname: Long surname: Wei fullname: Wei, Long organization: Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, School of Physical Sciences, University of Chinese Academy of Sciences |
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| Cites_doi | 10.1118/1.1576394 10.1088/1361-6560/aa8a4b 10.1002/mp.12096 10.1088/0031-9155/59/18/5457 10.1118/1.595025 10.1038/srep24454 10.1002/mp.13001 10.1016/j.jvcir.2012.04.003 10.3233/XST-17272 10.1016/j.nima.2008.03.017 10.4316/AECE.2018.04012 10.1016/j.nima.2005.03.104 10.1118/1.3525840 10.1118/1.595958 10.1088/0031-9155/61/10/3784 10.1016/j.nima.2009.03.141 10.1016/j.sigpro.2013.03.005 10.1088/0031-9155/21/5/002 10.1088/1361-6420/aa942c 10.1016/j.heliyon.2017.e00393 10.1118/1.2987668 10.1148/radiol.14132732 10.1109/TMI.2016.2532122 10.1118/1.4947485 10.1088/0031-9155/61/10/3749 10.1118/1.3681273 10.1109/ACCESS.2018.2858196 10.1118/1.4870375 10.1109/TMI.2014.2320284 10.1016/j.sigpro.2010.03.016 10.1118/1.3570658 10.1088/0031-9155/33/4/005 10.1109/TMI.2017.2715284 10.1016/j.neucom.2013.09.055 10.1109/ICBBE.2009.5163756 10.1117/12.2236588 |
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| Keywords | Material decomposition Dual-energy CT Photon counting Noise reduction Autoencoder |
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| References | Firsching, Talla, Michel, Anton (CR10) 2008; 591 Ding, Klopfer, Ducote, Masaki, Molloi (CR13) 2014; 272 Wang, Liu, Xia, Dong, Luo, Huang, Feng (CR31) 2013; 93 Liu, Wang, Luo, Zhu, Ye (CR30) 2012; 23 Li, Li, Luo, Tang, Mao, Xiaoye (CR47) 2013; 2013 Harms, Wang, Petrongolo, Niu, Zhu (CR24) 2016; 43 Cheng, Ni, Chou, Qin, Tiu, Chang, Huang, Shen, Chen (CR39) 2016; 6 Alvarez (CR5) 2011; 38 Granton, Pollmann, Ford, Drangova, Holdsworth (CR11) 2008; 35 CR18 CR38 Lehmann, Alvarez, Macovski, Brody, Pelc, Riederer, Hall (CR2) 1981; 8 Long, Fessler (CR7) 2014; 33 CR36 Dufan, Zhang, Zhu, Xiaofei, Wang (CR48) 2016; 61 Kalender, Perman, Vetter, Klotz (CR3) 1986; 13 CR33 Ding, Ducote, Molloi (CR22) 2012; 39 Niu, Dong, Petrongolo, Zhu (CR35) 2014; 41 Kallenberg, Petersen, Nelsen, Ng, Diao, Igel, Vachon, Holland, Winkel, Karssemeijer, Lillholm (CR40) 2016; 35 Barber, Sidky, Schmidt, Pan (CR15) 2016; 61 You, Yang, Shan, Gjesteby, Li, Shenghong, Zhang, Zhao, Zhang, Cong, Wang (CR45) 2018; 6 Chuang, Huang (CR19) 1988; 33 Tanyeri, Demirci (CR27) 2018; 18 Chen, Dapeng (CR32) 2010; 90 Hata, Akhand, Murase (CR41) 2017; 8 Chen, Zhang, Kalra, Lin, Chen, Liao, Zhou, Wang (CR34) 2017; 36 Xue, Ruan, Xinhua, Kuang, Wang, Long, Niu (CR25) 2017; 44 Nishio, Nagashima, Hirabayashi, Ohnishi, Sasaki, Sagawa, Hamada, Yamashita (CR43) 2017; 3 CR8 CR29 CR28 Lee, Choi, Kim (CR6) 2014; 59 CR46 Chen, Zhang, Sidky, Pan (CR16) 2017; 62 Lin, Zhang, Huang, Bian, Zhang, Wang, Liao, Li, Zhang, Zeng, Ma (CR23) 2018; 26 CR44 Firsching, Butler, Scott, Anderson, Michel, Anton (CR12) 2009; 607 CR20 CR42 Le, Molloi (CR21) 2011; 38 Alvarez, Macovski (CR1) 1976; 21 Ding, Niu, Zhang, Long (CR26) 2018; 45 Dong, Niu, Zhu (CR14) 2014; 41 Niu, Yu, Ma, Wang (CR17) 2018; 34 Kappadath, Shaw (CR4) 2006; 30 Giersch, Firsching, Niederlöhner, Anton (CR9) 2005; 546 Liou, Cheng, Liou, Liou (CR37) 2014; 139 B Chen (122_CR16) 2017; 62 122_CR44 122_CR46 X Dong (122_CR14) 2014; 41 LA Lehmann (122_CR2) 1981; 8 122_CR20 H Ding (122_CR22) 2012; 39 U Tanyeri (122_CR27) 2018; 18 122_CR42 Y Xue (122_CR25) 2017; 44 Q Chen (122_CR32) 2010; 90 R Hata (122_CR41) 2017; 8 122_CR8 Q Liu (122_CR30) 2012; 23 K-S Chuang (122_CR19) 1988; 33 C-Y Liou (122_CR37) 2014; 139 S Wang (122_CR31) 2013; 93 RE Alvarez (122_CR1) 1976; 21 M Firsching (122_CR12) 2009; 607 122_CR18 T Niu (122_CR35) 2014; 41 SC Kappadath (122_CR4) 2006; 30 122_CR36 122_CR38 122_CR33 S Lee (122_CR6) 2014; 59 PV Granton (122_CR11) 2008; 35 Y Long (122_CR7) 2014; 33 H Chen (122_CR34) 2017; 36 C You (122_CR45) 2018; 6 RF Barber (122_CR15) 2016; 61 W Dufan (122_CR48) 2016; 61 J Giersch (122_CR9) 2005; 546 M Kallenberg (122_CR40) 2016; 35 WA Kalender (122_CR3) 1986; 13 J-Z Cheng (122_CR39) 2016; 6 R Alvarez (122_CR5) 2011; 38 S Niu (122_CR17) 2018; 34 122_CR29 J Lin (122_CR23) 2018; 26 M Nishio (122_CR43) 2017; 3 B Li (122_CR47) 2013; 2013 H Ding (122_CR13) 2014; 272 HQ Le (122_CR21) 2011; 38 J Harms (122_CR24) 2016; 43 Q Ding (122_CR26) 2018; 45 122_CR28 M Firsching (122_CR10) 2008; 591 |
| References_xml | – volume: 30 start-page: 1110 year: 2006 end-page: 1117 ident: CR4 article-title: Dual-energy digital mammography: calibration and inverse-mapping techniques to estimate calcification thickness and glandular-tissue ratio publication-title: Med. Phys. doi: 10.1118/1.1576394 – ident: CR18 – volume: 62 start-page: 8763 year: 2017 end-page: 8793 ident: CR16 article-title: Image reconstruction and scan configurations enabled by optimization-based algorithms in multispectral CT publication-title: Phys. Med. Biol. doi: 10.1088/1361-6560/aa8a4b – volume: 44 start-page: 886 year: 2017 end-page: 901 ident: CR25 article-title: Statistical image-domain multimaterial decomposition for dual-energy CT publication-title: Med. Phys. doi: 10.1002/mp.12096 – volume: 59 start-page: 5457 year: 2014 end-page: 5482 ident: CR6 article-title: Quantitative material decomposition using spectral computed tomography with an energy-resolved photon-counting detector publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/59/18/5457 – volume: 8 start-page: 659 year: 1981 end-page: 667 ident: CR2 article-title: Generalized image combinations in dual KVP digital radiography publication-title: Med. Phys. doi: 10.1118/1.595025 – volume: 6 start-page: 24454 year: 2016 ident: CR39 article-title: Computer-aided diagnosis with deep learning architecture: applications to breast lesions in US images and pulmonary nodules in CT scans publication-title: Sci. Rep. doi: 10.1038/srep24454 – volume: 45 start-page: 3614 year: 2018 end-page: 3626 ident: CR26 article-title: Image-domain multimaterial decomposition for dual-energy CT based on prior information of material images publication-title: Med. Phys. doi: 10.1002/mp.13001 – volume: 23 start-page: 753 year: 2012 end-page: 766 ident: CR30 article-title: An augmented Lagrangian approach to general dictionary learning for image denoising publication-title: J. Vis. Commun. Image Represent. doi: 10.1016/j.jvcir.2012.04.003 – volume: 26 start-page: 311 year: 2018 end-page: 330 ident: CR23 article-title: Iterative reconstruction for low does dual energy CT using information-divergence constrained spectral redundancy information publication-title: J. X-ray Sci. Technol. doi: 10.3233/XST-17272 – volume: 591 start-page: 19 year: 2008 end-page: 23 ident: CR10 article-title: Material resolving X-ray imaging using spectrum reconstruction with Medipix2 publication-title: Nucl. Instrum. Methods Phys. Res. A doi: 10.1016/j.nima.2008.03.017 – ident: CR33 – volume: 2013 start-page: 1 year: 2013 end-page: 8 ident: CR47 article-title: Simultaneous reduction in noise and cross-contamination artifacts for dual-energy X-ray CT publication-title: Biomed. Res. Int. – volume: 18 start-page: 99 year: 2018 end-page: 106 ident: CR27 article-title: Wavelet-based adaptive anisotropic diffusion filter publication-title: Adv. Electr. Comput. Eng. doi: 10.4316/AECE.2018.04012 – volume: 546 start-page: 125 year: 2005 end-page: 130 ident: CR9 article-title: Material reconstruction with spectroscopic pixel X-ray detectors publication-title: Nucl. Instrum. Methods Phys. Res. A doi: 10.1016/j.nima.2005.03.104 – ident: CR29 – volume: 38 start-page: 245 year: 2011 end-page: 255 ident: CR21 article-title: Least squares parameter estimation methods for material decomposition with energy discriminating detectors publication-title: Med. Phys. doi: 10.1118/1.3525840 – volume: 13 start-page: 334 year: 1986 end-page: 339 ident: CR3 article-title: Evaluation of a prototype dual-energy computed tomographic apparatus publication-title: Med. Phys. doi: 10.1118/1.595958 – ident: CR8 – volume: 61 start-page: 3784 year: 2016 end-page: 3818 ident: CR15 article-title: An algorithm for constrained one-step inversion of spectral CT data publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/61/10/3784 – volume: 607 start-page: 179 year: 2009 end-page: 182 ident: CR12 article-title: Contrast agent recognition in small animal CT using the Medipix2 detector publication-title: Nucl. Instrum. Methods Phys. Res. A doi: 10.1016/j.nima.2009.03.141 – volume: 93 start-page: 2696 year: 2013 end-page: 2708 ident: CR31 article-title: Dictionary learning based impulse noise removal via L1–L1 minimization publication-title: Signal Process. doi: 10.1016/j.sigpro.2013.03.005 – ident: CR42 – volume: 21 start-page: 733 year: 1976 end-page: 744 ident: CR1 article-title: Energy-selective reconstruction in X-ray computerized tomography publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/21/5/002 – volume: 34 start-page: 024003 year: 2018 ident: CR17 article-title: Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction publication-title: Inverse Probl. doi: 10.1088/1361-6420/aa942c – volume: 3 start-page: e00393 year: 2017 ident: CR43 article-title: Convolutional auto-encoder for image denoising of ultra-low-dose CT publication-title: Heliyon doi: 10.1016/j.heliyon.2017.e00393 – volume: 35 start-page: 5030 year: 2008 end-page: 5042 ident: CR11 article-title: Implementation of dual- and triple-energy cone-beam micro-CT for postreconstruction material decomposition publication-title: Med. Phys. doi: 10.1118/1.2987668 – volume: 272 start-page: 731 year: 2014 end-page: 738 ident: CR13 article-title: Breast tissue characterization with photon-counting spectral CT imaging: a postmortem breast study publication-title: Radiology doi: 10.1148/radiol.14132732 – volume: 8 start-page: 19 year: 2017 end-page: 26 ident: CR41 article-title: Multi-valued autoencoders and classification of large-scale multi-class problem publication-title: Int. J. Adv. Comput. Sci. Appl. – ident: CR46 – ident: CR44 – volume: 35 start-page: 1322 year: 2016 end-page: 1331 ident: CR40 article-title: Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2016.2532122 – volume: 43 start-page: 2676 year: 2016 end-page: 2686 ident: CR24 article-title: Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization publication-title: Med. Phys. doi: 10.1118/1.4947485 – ident: CR38 – volume: 61 start-page: 3749 year: 2016 end-page: 3783 ident: CR48 article-title: A weighted polynomial based material decomposition method for spectral x-ray CT imaging publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/61/10/3749 – volume: 39 start-page: 1289 year: 2012 end-page: 1297 ident: CR22 article-title: Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system publication-title: Med. Phys. doi: 10.1118/1.3681273 – volume: 6 start-page: 41839 year: 2018 end-page: 41855 ident: CR45 article-title: Structurally-sensitive multi-scale deep neural network for low-dose CT denosing publication-title: IEEE Access. doi: 10.1109/ACCESS.2018.2858196 – volume: 41 start-page: 051909 year: 2014 ident: CR14 article-title: Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization publication-title: Med. Phys. doi: 10.1118/1.4870375 – volume: 33 start-page: 1614 year: 2014 end-page: 1626 ident: CR7 article-title: Multi-material decomposition using statistical image reconstruction for spectral CT publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2014.2320284 – volume: 90 start-page: 2778 year: 2010 end-page: 2783 ident: CR32 article-title: Image denoising by bounded block matching and 3D filtering publication-title: Signal Process. doi: 10.1016/j.sigpro.2010.03.016 – ident: CR36 – volume: 38 start-page: 2324 year: 2011 end-page: 2334 ident: CR5 article-title: Estimator for photon counting energy selective X-ray imaging with multibin pulse height analysis publication-title: Med. Phys. doi: 10.1118/1.3570658 – volume: 33 start-page: 455 year: 1988 end-page: 466 ident: CR19 article-title: Comparison of four dual energy image decomposition methods publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/33/4/005 – volume: 36 start-page: 2524 year: 2017 end-page: 2535 ident: CR34 article-title: Low-dose CT with a residual encoder-decoder convolutional neural network publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2017.2715284 – volume: 139 start-page: 84 year: 2014 end-page: 96 ident: CR37 article-title: Autoencoder for words publication-title: Neurocomputing doi: 10.1016/j.neucom.2013.09.055 – volume: 41 start-page: 041901-1 year: 2014 end-page: 041901-10 ident: CR35 article-title: Iterative image-domain decomposition for dual-energy CT publication-title: Med. Phys. – ident: CR28 – ident: CR20 – volume: 23 start-page: 753 year: 2012 ident: 122_CR30 publication-title: J. Vis. Commun. Image Represent. doi: 10.1016/j.jvcir.2012.04.003 – volume: 26 start-page: 311 year: 2018 ident: 122_CR23 publication-title: J. X-ray Sci. Technol. doi: 10.3233/XST-17272 – volume: 30 start-page: 1110 year: 2006 ident: 122_CR4 publication-title: Med. Phys. doi: 10.1118/1.1576394 – volume: 43 start-page: 2676 year: 2016 ident: 122_CR24 publication-title: Med. Phys. doi: 10.1118/1.4947485 – volume: 13 start-page: 334 year: 1986 ident: 122_CR3 publication-title: Med. Phys. doi: 10.1118/1.595958 – volume: 35 start-page: 5030 year: 2008 ident: 122_CR11 publication-title: Med. Phys. doi: 10.1118/1.2987668 – volume: 39 start-page: 1289 year: 2012 ident: 122_CR22 publication-title: Med. Phys. doi: 10.1118/1.3681273 – ident: 122_CR28 doi: 10.1109/ICBBE.2009.5163756 – ident: 122_CR20 – ident: 122_CR29 – ident: 122_CR18 doi: 10.1117/12.2236588 – volume: 36 start-page: 2524 year: 2017 ident: 122_CR34 publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2017.2715284 – volume: 35 start-page: 1322 year: 2016 ident: 122_CR40 publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2016.2532122 – ident: 122_CR8 – volume: 8 start-page: 659 year: 1981 ident: 122_CR2 publication-title: Med. Phys. doi: 10.1118/1.595025 – volume: 21 start-page: 733 year: 1976 ident: 122_CR1 publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/21/5/002 – volume: 18 start-page: 99 year: 2018 ident: 122_CR27 publication-title: Adv. Electr. Comput. Eng. doi: 10.4316/AECE.2018.04012 – volume: 6 start-page: 24454 year: 2016 ident: 122_CR39 publication-title: Sci. Rep. doi: 10.1038/srep24454 – ident: 122_CR33 – ident: 122_CR36 – volume: 139 start-page: 84 year: 2014 ident: 122_CR37 publication-title: Neurocomputing doi: 10.1016/j.neucom.2013.09.055 – volume: 59 start-page: 5457 year: 2014 ident: 122_CR6 publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/59/18/5457 – volume: 272 start-page: 731 year: 2014 ident: 122_CR13 publication-title: Radiology doi: 10.1148/radiol.14132732 – volume: 2013 start-page: 1 year: 2013 ident: 122_CR47 publication-title: Biomed. Res. Int. – volume: 61 start-page: 3749 year: 2016 ident: 122_CR48 publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/61/10/3749 – volume: 591 start-page: 19 year: 2008 ident: 122_CR10 publication-title: Nucl. Instrum. Methods Phys. Res. A doi: 10.1016/j.nima.2008.03.017 – volume: 90 start-page: 2778 year: 2010 ident: 122_CR32 publication-title: Signal Process. doi: 10.1016/j.sigpro.2010.03.016 – ident: 122_CR38 – volume: 61 start-page: 3784 year: 2016 ident: 122_CR15 publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/61/10/3784 – volume: 6 start-page: 41839 year: 2018 ident: 122_CR45 publication-title: IEEE Access. doi: 10.1109/ACCESS.2018.2858196 – ident: 122_CR44 – ident: 122_CR42 – volume: 546 start-page: 125 year: 2005 ident: 122_CR9 publication-title: Nucl. Instrum. Methods Phys. Res. A doi: 10.1016/j.nima.2005.03.104 – volume: 93 start-page: 2696 year: 2013 ident: 122_CR31 publication-title: Signal Process. doi: 10.1016/j.sigpro.2013.03.005 – volume: 38 start-page: 2324 year: 2011 ident: 122_CR5 publication-title: Med. Phys. doi: 10.1118/1.3570658 – volume: 41 start-page: 051909 year: 2014 ident: 122_CR14 publication-title: Med. Phys. doi: 10.1118/1.4870375 – volume: 38 start-page: 245 year: 2011 ident: 122_CR21 publication-title: Med. Phys. doi: 10.1118/1.3525840 – volume: 33 start-page: 1614 year: 2014 ident: 122_CR7 publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2014.2320284 – volume: 33 start-page: 455 year: 1988 ident: 122_CR19 publication-title: Phys. Med. Biol. doi: 10.1088/0031-9155/33/4/005 – ident: 122_CR46 – volume: 45 start-page: 3614 year: 2018 ident: 122_CR26 publication-title: Med. Phys. doi: 10.1002/mp.13001 – volume: 8 start-page: 19 year: 2017 ident: 122_CR41 publication-title: Int. J. Adv. Comput. Sci. Appl. – volume: 44 start-page: 886 year: 2017 ident: 122_CR25 publication-title: Med. Phys. doi: 10.1002/mp.12096 – volume: 3 start-page: e00393 year: 2017 ident: 122_CR43 publication-title: Heliyon doi: 10.1016/j.heliyon.2017.e00393 – volume: 62 start-page: 8763 year: 2017 ident: 122_CR16 publication-title: Phys. Med. Biol. doi: 10.1088/1361-6560/aa8a4b – volume: 607 start-page: 179 year: 2009 ident: 122_CR12 publication-title: Nucl. Instrum. Methods Phys. Res. A doi: 10.1016/j.nima.2009.03.141 – volume: 34 start-page: 024003 year: 2018 ident: 122_CR17 publication-title: Inverse Probl. doi: 10.1088/1361-6420/aa942c – volume: 41 start-page: 041901-1 year: 2014 ident: 122_CR35 publication-title: Med. Phys. |
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A major challenge for the material decomposition task of the dual-energy computed tomography (DECT) is the algorithm often suffers from heavy noise in... |
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| Title | A study on noise reduction for dual-energy CT material decomposition with autoencoder |
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