{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T14:46:37Z","timestamp":1780929997051,"version":"3.54.1"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T00:00:00Z","timestamp":1667433600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T00:00:00Z","timestamp":1667433600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62173259"],"award-info":[{"award-number":["62173259"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61625305"],"award-info":[{"award-number":["61625305"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s11517-022-02698-7","type":"journal-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T03:02:31Z","timestamp":1667444551000},"page":"97-107","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Dynamic PET images denoising using spectral graph wavelet transform"],"prefix":"10.1007","volume":"61","author":[{"given":"Liqun","family":"Yi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6081-1759","authenticated-orcid":false,"given":"Yuxia","family":"Sheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Chai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingxin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,3]]},"reference":[{"key":"2698_CR1","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1016\/j.compbiomed.2014.04.014","volume":"50","author":"B Foster","year":"2014","unstructured":"Foster B, Bagci U, Mansoor A, Xu Z, Mollura DJ (2014) A review on segmentation of positron emission tomography images. Comput Biol Med 50:76\u201396","journal-title":"Comput Biol Med"},{"key":"2698_CR2","doi-asserted-by":"crossref","unstructured":"Mansoor A, Bagci U, Mollura DJ (2014) Optimally stabilized PET image denoising using trilateral filtering. In: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) (pp 130-137). Springer","DOI":"10.1007\/978-3-319-10404-1_17"},{"issue":"12","key":"2698_CR3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0081390","volume":"8","author":"J Dutta","year":"2013","unstructured":"Dutta J, Leahy RM, Li Q (2013) Non-local means denoising of dynamic PET images. PLoS ONE 8(12)","journal-title":"PLoS ONE"},{"issue":"2","key":"2698_CR4","doi-asserted-by":"publisher","first-page":"68","DOI":"10.31436\/iiumej.v19i2.835","volume":"19","author":"KB Khan","year":"2018","unstructured":"Khan KB, Shahid M, Ullah H, Rehman E, Khan MM (2018) Adaptive trimmed mean autoregressive model for reduction of poisson noise in scintigraphic images. IIUM Engineering Journal 19(2):68\u201379","journal-title":"IIUM Engineering Journal"},{"key":"2698_CR5","doi-asserted-by":"crossref","unstructured":"Khan KB, Khaliq AA, Shahid M, Ullah H (2016) Poisson noise reduction in scintigraphic images using gradient adaptive trimmed mean filter. In: 2016 International Conference on Intelligent Systems Engineering (ICISE) (pp. 301-305). IEEE","DOI":"10.1109\/INTELSE.2016.7475138"},{"issue":"6","key":"2698_CR6","first-page":"1755","volume":"23","author":"KB Khan","year":"2016","unstructured":"Khan KB, Khaliq AA, Shahid M, Shah JA (2016) A new approach of weighted gradient filter for denoising of medical images in the presence of poisson noise. Tehni\u010dki vjesnik 23(6):1755\u20131762","journal-title":"Tehni\u010dki vjesnik"},{"key":"2698_CR7","doi-asserted-by":"crossref","unstructured":"Ullah H, Amir M, Haq UII, Khan SU, Rahim MKA, Khan KB, (2018) Wavelet based de-noising using logarithmic shrinkage function. Wireless Personal Communications 98(1):1473\u20131488","DOI":"10.1007\/s11277-017-4927-3"},{"key":"2698_CR8","doi-asserted-by":"crossref","unstructured":"Chan C, Meikle S, Fulton R, Tian GJ, Cai W, Feng D (2009) A non-local post-filtering algorithm for PET incorporating anatomical knowledge. In: Nuclear Science Symposium Conference Record (NSS) (pp. 2728-2732). IEEE","DOI":"10.1109\/NSSMIC.2009.5401971"},{"issue":"3","key":"2698_CR9","doi-asserted-by":"publisher","first-page":"961","DOI":"10.1088\/0031-9155\/60\/3\/961","volume":"60","author":"J Yan","year":"2015","unstructured":"Yan J, Lim JCS, Townsend DW (2015) MRI-guided brain PET image filtering and partial volume correction. Phys Med Biol 60(3):961\u2013976","journal-title":"Phys Med Biol"},{"issue":"3","key":"2698_CR10","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1109\/TMI.2010.2076827","volume":"30","author":"S Somayajula","year":"2010","unstructured":"Somayajula S, Panagiotou C, Rangarajan A, Li Q, Arridge SR, Leahy RM (2010) PET image reconstruction using information theoretic anatomical priors. IEEE Trans Med Imaging 30(3):537\u2013549","journal-title":"IEEE Trans Med Imaging"},{"issue":"4","key":"2698_CR11","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/TCI.2019.2913287","volume":"5","author":"TA Song","year":"2019","unstructured":"Song TA, Yang F, Chowdhury SR, Kim K, Johnson KA, El Fakhri G, Li Q, Dutta J (2019) PET image deblurring and super-resolution with an MR-based joint entropy prior. IEEE Transactions on Computational Imaging 5(4):530\u2013539","journal-title":"IEEE Transactions on Computational Imaging"},{"key":"2698_CR12","doi-asserted-by":"crossref","unstructured":"Lu L, Hu D, Ma X, Ma J, Rahmim A, Chen W (2014) Dynamic PET denoising incorporating a composite image guided filter. In: Nuclear Science Symposium and Medical Imaging Conference (NSS\/MIC) (pp. 1-4). IEEE","DOI":"10.1109\/NSSMIC.2014.7430922"},{"issue":"6","key":"2698_CR13","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1109\/TRPMS.2018.2869936","volume":"2","author":"F Hashimoto","year":"2018","unstructured":"Hashimoto F, Ohba H, Ote K, Tsukada H (2018) Denoising of dynamic sinogram by image guided filtering for positron emission tomography. IEEE Transactions on Radiation and Plasma Medical Sciences 2(6):541\u2013548","journal-title":"IEEE Transactions on Radiation and Plasma Medical Sciences"},{"key":"2698_CR14","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.bspc.2017.11.002","volume":"41","author":"H Jomaa","year":"2018","unstructured":"Jomaa H, Mabrouk R, Khlifa N, Morain-Nicolier F (2018) Denoising of dynamic PET im-ages using a multi-scale transform and non-local means filter. Biomed Signal Process Control 41:69\u201380","journal-title":"Biomed Signal Process Control"},{"issue":"2","key":"2698_CR15","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1109\/TRPMS.2018.2877644","volume":"3","author":"K Gong","year":"2019","unstructured":"Gong K, Guan J, Liu CC, Qi J (2019) PET image denoising using a deep neural network through fine tuning. IEEE Transactions on Radiation and Plasma Medical Sciences 3(2):153\u2013161","journal-title":"IEEE Transactions on Radiation and Plasma Medical Sciences"},{"key":"2698_CR16","doi-asserted-by":"publisher","first-page":"52378","DOI":"10.1109\/ACCESS.2021.3069236","volume":"9","author":"H Sun","year":"2021","unstructured":"Sun H, Peng L, Zhang H, He Y, Cao S, Lu L (2021) Dynamic PET image denoising using deep image prior combined with regularization by denoising. IEEE Access 9:52378\u201352392","journal-title":"IEEE Access"},{"issue":"1","key":"2698_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TRPMS.2020.3014786","volume":"5","author":"AJ Reader","year":"2021","unstructured":"Reader AJ, Corda G, Mehranian A, Costa-Luis Cd, Ellis S, Schnabel JA (2021) Deep learning for PET image reconstruction. IEEE Transactions on Radiation and Plasma Medical Sciences 5(1):1\u201325","journal-title":"IEEE Transactions on Radiation and Plasma Medical Sciences"},{"issue":"13","key":"2698_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00259-019-04468-4","volume":"46","author":"J Cui","year":"2019","unstructured":"Cui J, Gong K, Guo N, Wu C, Meng XX, Kim K, Zheng K, Wu ZF, Fu LP, Xu BX, Zhu ZH, Tian JH, Liu HF (2019) PET image denoising using unsupervised deep learning. Eur J Nucl Med Mol Imaging 46(13):1\u201310","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"3","key":"2698_CR19","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1148\/radiol.2018180940","volume":"290","author":"KT Chen","year":"2018","unstructured":"Chen KT, Gong E, de Carvalho Macruz FB, Xu JS, Boumis A, Khalighi M, Poston KL, Sha SJ, Greicius MD, Mormino E, Pauly JM, Srinivas S, Zaharchuk G (2018) Ultra-low-dose 18F-Florbetaben amyloid PET imaging using deep learning with multi-contrast MRI inputs. Radiology 290(3):649\u2013656","journal-title":"Radiology"},{"issue":"3","key":"2698_CR20","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/MSP.2012.2235192","volume":"30","author":"DI Shuman","year":"2013","unstructured":"Shuman DI, Narang SK, Frossard P, Ortega A, Vandergheynst P (2013) The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains. IEEE Signal Process Mag 30(3):83\u201398","journal-title":"IEEE Signal Process Mag"},{"issue":"2","key":"2698_CR21","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.acha.2013.06.004","volume":"36","author":"FG Meyer","year":"2014","unstructured":"Meyer FG, Shen X (2014) Perturbation of the eigenvectors of the graph laplacian: Application to image denoising. Appl Comput Harmon Anal 36(2):326\u2013334","journal-title":"Appl Comput Harmon Anal"},{"key":"2698_CR22","doi-asserted-by":"crossref","unstructured":"Guo S, Sheng Y, Chai L, Zhang J (2019) Graph filtering approach to PET image denoising. In: 1st International Conference on Industrial Artificial Intelligence (IAI) (pp. 1-6). IEEE","DOI":"10.1109\/ICIAI.2019.8850802"},{"issue":"2","key":"2698_CR23","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.acha.2010.04.005","volume":"30","author":"DK Hammond","year":"2011","unstructured":"Hammond DK, Vandergheynst P, Gribonval R (2011) Wavelets on graphs via spectral graph theory. Appl Comput Harmon Anal 30(2):129\u2013150","journal-title":"Appl Comput Harmon Anal"},{"key":"2698_CR24","doi-asserted-by":"crossref","unstructured":"Deutsch S, Ortega A, Medioni G (2016) Manifold denoising based on spectral graph wavelets. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4673-46777). IEEE","DOI":"10.1109\/ICASSP.2016.7472563"},{"issue":"1","key":"2698_CR25","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TMI.2014.2343916","volume":"34","author":"G Wang","year":"2014","unstructured":"Wang G, Qi J (2014) PET image reconstruction using kernel method. IEEE Trans Med Imaging 34(1):61\u201371","journal-title":"IEEE Trans Med Imaging"},{"issue":"11","key":"2698_CR26","doi-asserted-by":"publisher","first-page":"1410","DOI":"10.1109\/TMI.2006.883453","volume":"25","author":"B Aubert-Broche","year":"2006","unstructured":"Aubert-Broche B, Griffin M, Pike GB, Evans AC, Collins DL (2006) Twenty new digital brain phantoms for creation of validation image data bases. IEEE Trans Med Imaging 25(11):1410\u20131416","journal-title":"IEEE Trans Med Imaging"},{"key":"2698_CR27","doi-asserted-by":"crossref","unstructured":"Buades A, Coll B, Morel JM (2005) A non-local algorithm for image denoising. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 60-65). IEEE","DOI":"10.1109\/CVPR.2005.38"},{"issue":"4","key":"2698_CR28","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1109\/4233.681168","volume":"1","author":"D Feng","year":"1997","unstructured":"Feng D, Wong KP, Wu CM, Siu WC (1997) A technique for extracting physiological parameters and the required input function simultaneously from PET image measurements: Theory and simulation study. IEEE Trans Inf Technol Biomed 1(4):243\u2013254","journal-title":"IEEE Trans Inf Technol Biomed"},{"issue":"4","key":"2698_CR29","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"issue":"4","key":"2698_CR30","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1002\/jmri.21049","volume":"27","author":"CR Jack","year":"2008","unstructured":"Jack CR, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, Weiner MW et al (2008) The alzheimer\u2019s disease neuroimaging initiative (ADNI): MRI methods. J Magn Reson Imaging 27(4):685\u2013691","journal-title":"J Magn Reson Imaging"},{"issue":"3","key":"2698_CR31","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1109\/MSP.2018.2887284","volume":"36","author":"X Dong","year":"2019","unstructured":"Dong X, Dorina T, Rabbat M, Frossard P (2019) Learning graphs from data: A signal representation perspective. IEEE Signal Process Mag 36(3):44\u201363","journal-title":"IEEE Signal Process Mag"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-022-02698-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-022-02698-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-022-02698-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T04:04:30Z","timestamp":1728273870000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-022-02698-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,3]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["2698"],"URL":"https:\/\/doi.org\/10.1007\/s11517-022-02698-7","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,3]]},"assertion":[{"value":"12 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 November 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}