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3D Tensor Based Nonlocal Low Rank Approximation in Dynamic PET Reconstruction

Nuobei Xie, Yunmei Chen, Huafeng Liu
<span title="2019-12-01">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
In this paper, we develop a novel tensor based nonlocal low-rank framework for dynamic PET reconstruction.  ...  Reconstructing images from multi-view projections is a crucial task both in the computer vision community and in the medical imaging community, and dynamic positron emission tomography (PET) is no exception  ...  Total Variation Regularization in Dynamic PET Apart from nonlocal low-rank tensor regularization, we also incorporate the total variation [40] (TV) as a complementary constraint into the dynamic PET  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19235299">doi:10.3390/s19235299</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31805743">pmid:31805743</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6928938/">pmcid:PMC6928938</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yslvbcnle5d27kjzt7lyj2fjd4">fatcat:yslvbcnle5d27kjzt7lyj2fjd4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200214011012/https://res.mdpi.com/d_attachment/sensors/sensors-19-05299/article_deploy/sensors-19-05299-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5f/f1/5ff146d2021ed9ea4c1e0f9c40d92be1b110ed5f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19235299"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928938" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

2014 Index IEEE Transactions on Medical Imaging Vol. 33

<span title="">2014</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yhnt2pif75h2bmnnmdg7m6nlc4" style="color: black;">IEEE Transactions on Medical Imaging</a> </i> &nbsp;
., +, TMI Feb. 2014 351-361 Low-Rank Modeling of Local -Space Neighborhoods (LORAKS) for Constrained MRI. Haldar, J.  ...  ., +, TMI Aug. 2014 1581-1591 Correction to "Total Variation-Stokes Strategy for Sparse-View X-ray CT Image Reconstruction" [Mar 14 749-763].  ...  MRI Upsampling Using Feature-Based Nonlocal Means Approach. Jafari-Khouzani, K., 1969 -1985 Numerical Surrogates for Human Observers in Myocardial Motion Evaluation From SPECT Images.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmi.2014.2386278">doi:10.1109/tmi.2014.2386278</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/poarfhfto5bm5mhfl7ugwtw4xy">fatcat:poarfhfto5bm5mhfl7ugwtw4xy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20151007100800/http://ieeexplore.ieee.org/ielx7/42/6966828/06998119.pdf?tp=&amp;arnumber=6998119&amp;isnumber=6966828" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9e/2d/9e2d1accca3a30b5e6d6f6f5eac49dfc800893e5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmi.2014.2386278"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Helical CT Reconstruction from Sparse-view Data through Exploiting the 3D Anatomical Structure Sparsity

Yongbo Wang, Gaofeng Chen, Xi Tao, Zhaoying Bian, Dong Zeng, Habib Zaidi, Ji He, Jianhua Ma
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Based on the analyses, we proposed a tensor decomposition and anisotropic total variation regularization model (TDATV) for SHCT reconstruction.  ...  INDEX TERMS Helical CT, sparse-view, tensor, total variation, iterative reconstruction.  ...  The low-rank priors are also explored to constrain the correlation between different image frames, e.g., between multi-energybin images in energy-resolved CT and time sequence images in perfusion CT [  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3049181">doi:10.1109/access.2021.3049181</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xu44rurg7jcp7gehhbrd6rijwm">fatcat:xu44rurg7jcp7gehhbrd6rijwm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716022927/https://archive-ouverte.unige.ch/files/downloads/0/0/1/4/8/8/7/2/unige_148872_attachment01.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/47/ed/47ed74ff6df8e8ff34527ad9d9f95fbddf710384.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3049181"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Front Matter: Volume 9412

Proceedings of SPIE, Christoph Hoeschen, Despina Kontos, Thomas G. Flohr
<span title="2015-04-28">2015</span> <i title="SPIE"> Medical Imaging 2015: Physics of Medical Imaging </i> &nbsp;
noise model (Best Student Paper Award) [9412-6] 9412 08 Fat-constrained 18 F-FDG PET reconstruction using Dixon MR imaging and the origin ensemble algorithm [9412-7] 9412 09 Feasibility of CT-based 3D  ...  Rank-sparsity constrained spectro-temporal reconstruction for retrospectively gated dynamic CT [9412-10] SESSION 3 DETECTOR TECHNOLOGY 0C Low-dose performance of wafer-scale CMOS-based x-ray detectors  ...  and microCT investigation [9412-138] 9412 3S A clinical evaluation of total variation-Stokes image reconstruction strategy for low-dose CT imaging of the chest [9412-139] 9412 3T CBCT reconstruction  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2184295">doi:10.1117/12.2184295</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ewelisqkxvbwbnxeiwhldcrfpi">fatcat:ewelisqkxvbwbnxeiwhldcrfpi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719114058/https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9412/941201/Front-Matter-Volume-9412/10.1117/12.2184295.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/55/6c/556c36ac5b156b1b5122db80d0db4e60c64bc68c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2184295"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Joint solution for PET image segmentation, denoising, and partial volume correction

Ziyue Xu, Mingchen Gao, Georgios Z. Papadakis, Brian Luna, Sanjay Jain, Daniel J. Mollura, Ulas Bagci
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kpkfymbkufcnzjfc5ydyokby4y" style="color: black;">Medical Image Analysis</a> </i> &nbsp;
Segmentation, denoising, and partial volume correction (PVC) are three major processes in the quantification of uptake regions in post-reconstruction PET images.  ...  Segmentation-PET image segmentation aims at separating and delineating the PET image into different uptake regions. Several methods have been proposed for PET image Xu et al.  ...  However, the opposite is not true for low count PET image.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.media.2018.03.007">doi:10.1016/j.media.2018.03.007</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29627687">pmid:29627687</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6080255/">pmcid:PMC6080255</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7o46n7a37zb2tavtbg2krg4rly">fatcat:7o46n7a37zb2tavtbg2krg4rly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209073445/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6080255&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/53/0a/530a0dc5d30ed09d37bbb97663a1713b2d5b8ca4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.media.2018.03.007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080255" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning [article]

Saiprasad Ravishankar, Jong Chul Ye, Jeffrey A. Fessler
<span title="2019-06-26">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper focuses on the two most recent trends in medical image reconstruction: methods based on sparsity or low-rank models, and data-driven methods based on machine learning techniques.  ...  These methods typically involve mathematical image models involving assumptions such as sparsity or low-rank.  ...  Sections III and IV describe sparsity and low-rank based approaches for image reconstruction.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.02816v2">arXiv:1904.02816v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ehahzrib2ff3dl5yl6pa7xpf24">fatcat:ehahzrib2ff3dl5yl6pa7xpf24</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200824154617/https://arxiv.org/pdf/1904.02816v1.pdf" title="fulltext PDF download [not primary version]" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/20/90/20909ead19b76634de3b1f4fdabb559cd65cf28b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.02816v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Front Matter: Volume 10574

Proceedings of SPIE, Elsa D. Angelini, Bennett A. Landman
<span title="2018-05-08">2018</span> <i title="SPIE"> Medical Imaging 2018: Image Processing </i> &nbsp;
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication.  ...  .  The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. These two-number sets start with 00, 01, 02, 03,  ...  10574 0C An effective fully deep convolutional neural networks for mitochondria segmentation based on ATUM-SEM SESSION 3 IMAGE ENHANCEMENT 0D A log-Euclidean and total variation based variational  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2315755">doi:10.1117/12.2315755</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jdfbaent6vhu5dwlrqrqt66vce">fatcat:jdfbaent6vhu5dwlrqrqt66vce</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190426060100/https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10574/1057401/Front-Matter-Volume-10574/10.1117/12.2315755.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bd/7c/bd7cbb19ba686cfbfa637c7790ba90bc9f35a135.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2315755"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Artifact Removal using Improved GoogLeNet for Sparse-view CT Reconstruction

Shipeng Xie, Xinyu Zheng, Yang Chen, Lizhe Xie, Jin Liu, Yudong Zhang, Jingjie Yan, Hu Zhu, Yining Hu
<span title="2018-04-30">2018</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with both accelerated scan and reduced projection/back-projection calculation.  ...  Despite the rapid developments, image noise and artifacts still remain a major issue in the low dose protocol.  ...  Acknowledgements The authors thank the anonymous referees for their constructive and insightful comments, which greatly improved the presentation of our research results.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-018-25153-w">doi:10.1038/s41598-018-25153-w</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29712978">pmid:29712978</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5928081/">pmcid:PMC5928081</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5awybf655ra4hdatnmp4cmtjiu">fatcat:5awybf655ra4hdatnmp4cmtjiu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719215134/https://lra.le.ac.uk/bitstream/2381/42119/3/s41598-018-25153-w.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/63/33/6333235ee65f1661111e514565a7aa4988c0380c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-018-25153-w"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5928081" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction [article]

Qiaoqiao Ding, Hui Ji, Yuhui Quan, Xiaoqun Zhang
<span title="2022-05-01">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In recent years, supervised deep learning has been extensively studied for LDCT image reconstruction, which trains a network over a dataset containing many pairs of normal-dose and low-dose images.  ...  The proposed method is built on a re-parametrization technique for Bayesian inference via deep network with random weights, combined with additional total variational (TV) regularization.  ...  Acknowledgement This work was supported by the NSFC (grant no. 12090024) and the Sino-German Mobility Programme (M-0187) by Sino-German Center for Research Promotion.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2205.00463v1">arXiv:2205.00463v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fu3yen6cdrfmfpiy6l3z4qqrgy">fatcat:fu3yen6cdrfmfpiy6l3z4qqrgy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220506181347/https://arxiv.org/pdf/2205.00463v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/50/c0/50c09ded71d2f86d19a7beb6f21c1b4b743e32e7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2205.00463v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Total Variation Regularization Algorithms for Images Corrupted with Different Noise Models: A Review

Paul Rodríguez
<span title="">2013</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ak4drtjatbcoxpgx5twsmzrwve" style="color: black;">Journal of Electrical and Computer Engineering</a> </i> &nbsp;
Total Variation (TV) regularization has evolved from an image denoising method for images corrupted with Gaussian noise into a more general technique for inverse problems such as deblurring, blind deconvolution  ...  , and inpainting, which also encompasses the Impulse, Poisson, Speckle, and mixed noise models.  ...  Well-known restoration algorithms include the bilateral filter [10] , Total Variation denoising [2] , the SUSAN filter [11] , Wavelet based denoising [12] , nonlocal means [13] , and so forth; several  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2013/217021">doi:10.1155/2013/217021</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kfqamwddznbk5jnjneieuaxdlu">fatcat:kfqamwddznbk5jnjneieuaxdlu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190302072633/http://pdfs.semanticscholar.org/9f7a/fdd77535e6003867ea4875406952eedfe23c.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9f/7a/9f7afdd77535e6003867ea4875406952eedfe23c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2013/217021"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> hindawi.com </button> </a>

MD-Recon-Net: A Parallel Dual-Domain Convolutional Neural Network for Compressed Sensing MRI [article]

Maosong Ran, Wenjun Xia, Yongqiang Huang, Zexin Lu, Peng Bao, Yan Liu, Huaiqiang Sun, Jiliu Zhou, Yi Zhang
<span title="2020-05-18">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Compressed sensing magnetic resonance imaging (CS-MRI) is a theoretical framework that can accurately reconstruct images from undersampled k-space data with a much lower sampling rate than the one set  ...  accurate MRI reconstruction.  ...  Typical transforms include Fourier transform (FT), wavelet, total variation (TV), and low-rank [8, [18] [19] [20] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1910.10392v2">arXiv:1910.10392v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/duu7ibfj5zfmdg5qk5a6zzk7km">fatcat:duu7ibfj5zfmdg5qk5a6zzk7km</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200520003027/https://arxiv.org/ftp/arxiv/papers/1910/1910.10392.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1910.10392v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Quantitative brain surface mapping of an electrophysiologic/metabolic mismatch in human neocortical epilepsy

Bálint Alkonyi, Csaba Juhász, Otto Muzik, Eishi Asano, Anita Saporta, Aashit Shah, Harry T. Chugani
<span title="">2009</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i5cvc2xxg5cvjfxxwkvdlht5zy" style="color: black;">Epilepsy Research</a> </i> &nbsp;
The spatial relationship between an intracranial EEG-defined epileptic focus and cortical hypometabolism on glucose PET has not been precisely described.  ...  cortical regions, we applied a novel, landmark-constrained conformal mapping approach in 14 children with refractory neocortical epilepsy.  ...  , Carole Klapko, CNMT and Mei-Li Lee, MS, for their expert technical assistance in performing the PET studies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.eplepsyres.2009.08.002">doi:10.1016/j.eplepsyres.2009.08.002</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/19734012">pmid:19734012</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3684207/">pmcid:PMC3684207</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fhuenqqztjbedee3fatx3c4qby">fatcat:fhuenqqztjbedee3fatx3c4qby</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200208182247/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC3684207&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7e/f7/7ef740abc8993a3788f34ceaf3c1fc91881dcdec.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.eplepsyres.2009.08.002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3684207" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A combined local and global motion estimation and compensation method for cardiac CT

Qiulin Tang, Beshan Chiang, Akinola Akinyemi, Alexander Zamyatin, Bibo Shi, Satoru Nakanishi, Bruce R. Whiting, Christoph Hoeschen
<span title="2014-03-19">2014</span> <i title="SPIE"> Medical Imaging 2014: Physics of Medical Imaging </i> &nbsp;
variation minimization filter for low dose CT imaging Total Variation (TV) minimization is a well known technique in image processing for image denoising.  ...  The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction (SART) technique coupled with the total variation minimization.  ...  evaluation, and improve patient care.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2043492">doi:10.1117/12.2043492</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fyzpc5m6jbh7fjohqpdmtzkhte">fatcat:fyzpc5m6jbh7fjohqpdmtzkhte</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20140308053954/http://spie.org:80/Documents/ConferencesExhibitions/MI14-Abstracts.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2043492"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

MToS: A Tree of Shapes for Multivariate Images

Edwin Carlinet, Thierry Geraud
<span title="">2015</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems.  ...  Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images.  ...  Lézoray for providing the rank images in Fig. 10 (d) , and the "Smart-Doc competition" team for having organized this challenge (and especially to Joseph Chazalon for having pointed out to us this challenge  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2015.2480599">doi:10.1109/tip.2015.2480599</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26415169">pmid:26415169</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j74f3dauvreplbanzq3lrp5xam">fatcat:j74f3dauvreplbanzq3lrp5xam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190426180544/https://hal.inria.fr/hal-01474835/file/carlinet.2015.itip.final.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b8/91/b8918ff910a980f8459628b651352714053b2f8e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2015.2480599"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Image Restoration for Low-dose CT via Transfer Learning and Residual Network

Anni Zhong, Bin Li, Ning Luo, Yuan Xu, Linghong Zhou, Xin Zhen
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
A residual network was implemented to effectively estimate the difference between denoised image and its original map, and a noisefree image was obtained by subtracting the residual map from the LDCT image  ...  Deep learning has recently been extensively investigated to remove artifacts in low-dose computed tomography (LDCT).  ...  ACKNOWLEDGMENT (Anni Zhong and Bin Li contributed equally to this work.)  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3002534">doi:10.1109/access.2020.3002534</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eeudji6wyzhx3mqgmctkv3ktsm">fatcat:eeudji6wyzhx3mqgmctkv3ktsm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429114948/https://ieeexplore.ieee.org/ielx7/6287639/8948470/09117103.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6b/67/6b67a79a294a73fc0dd5328ea1017d94a104920a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3002534"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>
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