{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T12:36:46Z","timestamp":1756384606289,"version":"3.40.4"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,12,29]],"date-time":"2024-12-29T00:00:00Z","timestamp":1735430400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,29]],"date-time":"2024-12-29T00:00:00Z","timestamp":1735430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"JSPS KAKENHI","award":["JP22K19501","JP22K04133","JP17H04116"],"award-info":[{"award-number":["JP22K19501","JP22K04133","JP17H04116"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"DOI":"10.1007\/s11548-024-03307-8","type":"journal-article","created":{"date-parts":[[2024,12,29]],"date-time":"2024-12-29T17:37:20Z","timestamp":1735493840000},"page":"665-676","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Fundamental study on improving the quality of X-ray fluorescence computed tomography images by applying deep image prior to projection images as a pre-denoising method"],"prefix":"10.1007","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9902-6866","authenticated-orcid":false,"given":"Sota","family":"Kusakari","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazuki","family":"Sato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuta","family":"Tsushima","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masahiro","family":"Matsuoka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tenta","family":"Sasaya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naoki","family":"Sunaguchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keisuke","family":"Matsubara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hidekazu","family":"Kawashima","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazuyuki","family":"Hyodo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tetsuya","family":"Yuasa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0499-9021","authenticated-orcid":false,"given":"Tsutomu","family":"Zeniya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,29]]},"reference":[{"key":"3307_CR1","doi-asserted-by":"publisher","first-page":"187","DOI":"10.2174\/157340506776930610","volume":"2","author":"M Larobina","year":"2006","unstructured":"Larobina M, Brunetti A, Salvatore M (2006) Small animal PET: a review of commercially available imaging systems. Curr Med Imaging Rev 2:187\u2013192. https:\/\/doi.org\/10.2174\/157340506776930610","journal-title":"Curr Med Imaging Rev"},{"key":"3307_CR2","doi-asserted-by":"publisher","DOI":"10.3389\/fphy.2014.00012","author":"C Kuntner","year":"2014","unstructured":"Kuntner C, Stout D (2014) Quantitative preclinical PET imaging: opportunities and challenges. Front Phys. https:\/\/doi.org\/10.3389\/fphy.2014.00012","journal-title":"Front Phys"},{"key":"3307_CR3","doi-asserted-by":"publisher","first-page":"R45","DOI":"10.1088\/0031-9155\/50\/22\/R01","volume":"50","author":"SR Meikle","year":"2005","unstructured":"Meikle SR, Kench P, Kassiou M, Banati RB (2005) Small animal SPECT and its place in the matrix of molecular imaging technologies. Phys Med Biol 50:R45\u2013R61. https:\/\/doi.org\/10.1088\/0031-9155\/50\/22\/R01","journal-title":"Phys Med Biol"},{"key":"3307_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2011\/796025","volume":"2011","author":"MM Khalil","year":"2011","unstructured":"Khalil MM, Tremoleda JL, Bayomy TB, Gsell W (2011) Molecular SPECT imaging: an overview. Int J Mol Imaging 2011:1\u201315. https:\/\/doi.org\/10.1155\/2011\/796025","journal-title":"Int J Mol Imaging"},{"key":"3307_CR5","doi-asserted-by":"publisher","first-page":"1721","DOI":"10.1109\/23.124168","volume":"38","author":"JP Hogan","year":"1991","unstructured":"Hogan JP, Gonsalves RA, Krieger AS (1991) Fluorescence computer tomography: a model for correction of X-ray absorption. IEEE Trans Nucl Sci 38:1721\u20131727. https:\/\/doi.org\/10.1109\/23.124168","journal-title":"IEEE Trans Nucl Sci"},{"key":"3307_CR6","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/23.554824","volume":"44","author":"T Yuasa","year":"1997","unstructured":"Yuasa T, Akiba M, Takeda T, Kazama M, Hoshino A, Watanabe Y, Hyodo K, Dilmanian FA, Akatsuka T, Itai Y (1997) Reconstruction method for flurescent X-ray computed tomography by least-squares method using singular value decomposition. IEEE Trans Nucl Sci 44:54\u201362. https:\/\/doi.org\/10.1109\/23.554824","journal-title":"IEEE Trans Nucl Sci"},{"key":"3307_CR7","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1107\/S0909049508031853","volume":"16","author":"T Takeda","year":"2009","unstructured":"Takeda T, Wu J, Thet-Thet-Lwin, Huo Q, Yuasa T, Hyodo K, Dilmanian FA, Akatsuka T (2009) X-ray fluorescent CT imaging of cerebral uptake of stable-iodine perfusion agent iodoamphetamine anolog IMP in mice. J Synchrotron Radiat 16:57\u201362. https:\/\/doi.org\/10.1107\/S0909049508031853","journal-title":"J Synchrotron Radiat"},{"key":"3307_CR8","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-05179-2","author":"T Sasaya","year":"2017","unstructured":"Sasaya T, Sunaguchi N, Hyodo K, Zeniya T, Yuasa T (2017) Multi-pinhole fluorescent x-ray computed tomography for molecular imaging. Sci Rep. https:\/\/doi.org\/10.1038\/s41598-017-05179-2","journal-title":"Sci Rep"},{"key":"3307_CR9","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.nima.2017.12.055","volume":"886","author":"T Sasaya","year":"2018","unstructured":"Sasaya T, Sunaguchi N, Seo SJ, Hyodo K, Zeniya T, Kim JK, Yuasa T (2018) Preliminary study on X-ray fluorescence computed tomography imaging of gold nanoparticles: acceleration of data acquisition by multiple pinholes scheme. Nucl Instrum Meth A 886:71\u201376. https:\/\/doi.org\/10.1016\/j.nima.2017.12.055","journal-title":"Nucl Instrum Meth A"},{"key":"3307_CR10","doi-asserted-by":"publisher","DOI":"10.1038\/srep22079","author":"N Manohar","year":"2016","unstructured":"Manohar N, Reynoso FJ, Diagaradjane P, Krishnan S, Cho SH (2016) Quantitative imaging of gold nanoparticle distribution in a tumor-bearing mouse using benchtop x-ray fluorescence computed tomography. Sci Rep. https:\/\/doi.org\/10.1038\/srep22079","journal-title":"Sci Rep"},{"key":"3307_CR11","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1109\/TMI.2019.2932014","volume":"39","author":"S Jung","year":"2020","unstructured":"Jung S, Kim T, Lee W, Kim H, Kim HS, Im HJ, Ye SJ (2020) Dynamic in vivo X-ray fluorescence imaging of gold in living mice exposed to gold nanoparticles. IEEE Trans Med Imaging 39:526\u2013533. https:\/\/doi.org\/10.1109\/TMI.2019.2932014","journal-title":"IEEE Trans Med Imaging"},{"key":"3307_CR12","doi-asserted-by":"publisher","first-page":"3910","DOI":"10.1109\/TMI.2020.3007165","volume":"39","author":"K Shaker","year":"2020","unstructured":"Shaker K, Vogt C, Katsu-Jimenez Y, Kuiper RV, Andersson K, Li Y, Larsson JC, Rodriguez-Garcia A, Toprak MS, Arsenian-Henriksson M, Hertz HM (2020) Longitudinal in-vivo X-Ray fluorescence computed tomography with molybdenum nanoparticles. IEEE Trans Med Imaging 39:3910\u20133919. https:\/\/doi.org\/10.1109\/TMI.2020.3007165","journal-title":"IEEE Trans Med Imaging"},{"key":"3307_CR13","doi-asserted-by":"publisher","first-page":"035020","DOI":"10.1088\/1361-6560\/acb3aa","volume":"68","author":"L Li","year":"2023","unstructured":"Li L, Zhang S, Zhang W, Lu H (2023) Full-field in vivo imaging of nanoparticles using benchtop cone-beam XFCT system with pixelated photon counting detector. Phys Med Biol 68:035020. https:\/\/doi.org\/10.1088\/1361-6560\/acb3aa","journal-title":"Phys Med Biol"},{"key":"3307_CR14","first-page":"307","volume-title":"Handbook on Synchrotron Radiation","author":"A Iida","year":"1991","unstructured":"Iida A, Gohshi Y (1991) Tracer element analysis by X-ray fluorescent. In: Ebashi S, Koch M, Rubenstein E (eds) Handbook on Synchrotron Radiation, vol 4. North Holland, pp 307\u2013438"},{"key":"3307_CR15","doi-asserted-by":"publisher","DOI":"10.1109\/NSSMIC.2008.4774392","author":"A Sawatzky","year":"2008","unstructured":"Sawatzky A, Brune C, Wubbeling F, Kosters T, Schafers K, Burger M (2008) Accurate EM-TV algorithm in PET with low SNR. IEEE Nuclear Sci Sympos Conf Record. https:\/\/doi.org\/10.1109\/NSSMIC.2008.4774392","journal-title":"IEEE Nuclear Sci Sympos Conf Record"},{"key":"3307_CR16","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s12149-021-01710-8","volume":"36","author":"K Matsubara","year":"2022","unstructured":"Matsubara K, Ibaraki M, Nemoto M, Watabe H, Kimura Y (2022) A review on AI in PET imaging. Ann Nucl Med 36:133\u2013143. https:\/\/doi.org\/10.1007\/s12149-021-01710-8","journal-title":"Ann Nucl Med"},{"key":"3307_CR17","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1007\/s12194-024-00780-3","volume":"17","author":"F Hashimoto","year":"2024","unstructured":"Hashimoto F, Onishi Y, Ote K, Tashima H, Reader AJ, Yamaya T (2024) Deep learning-based PET image denoising and reconstruction: a review. Radiol Phys Technol 17:24\u201346. https:\/\/doi.org\/10.1007\/s12194-024-00780-3","journal-title":"Radiol Phys Technol"},{"key":"3307_CR18","doi-asserted-by":"publisher","first-page":"1867","DOI":"10.1007\/s11263-020-01303-4","volume":"2020","author":"D Ulyanov","year":"2020","unstructured":"Ulyanov D, Vedaldi A, Lempitsky V (2020) Deep Image Prior. Int J Comput Vis 2020:1867\u20131888. https:\/\/doi.org\/10.1007\/s11263-020-01303-4","journal-title":"Int J Comput Vis"},{"key":"3307_CR19","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/TMI.2018.2888491","volume":"38","author":"K Gong","year":"2019","unstructured":"Gong K, Catane C, Qi J, Li Q (2019) PET image reconstruction using deep image prior. IEEE Trans Med Imaging 38:1655\u20131665. https:\/\/doi.org\/10.1109\/TMI.2018.2888491","journal-title":"IEEE Trans Med Imaging"},{"key":"3307_CR20","doi-asserted-by":"publisher","first-page":"96594","DOI":"10.1109\/ACCESS.2019.2929230","volume":"7","author":"F Hashimoto","year":"2019","unstructured":"Hashimoto F, Ohba H, Ote K, Teramoto A, Tsukada H (2019) Dynamic PET image denoising using deep convolutional neural networks without prior training datasets. IEEE Access 7:96594\u201396603. https:\/\/doi.org\/10.1109\/ACCESS.2019.2929230","journal-title":"IEEE Access"},{"doi-asserted-by":"publisher","unstructured":"Gong K, Kim K, Wu D, Kalra MK, Li Q (2019) Low-dose dual energy CT image reconstruction using non-local deep image prior. In: Proceedings of 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS\/MIC), Manchester, UK, pp 1\u20132. https:\/\/doi.org\/10.1109\/NSS\/MIC42101.2019.9060001","key":"3307_CR21","DOI":"10.1109\/NSS\/MIC42101.2019.9060001"},{"key":"3307_CR22","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.tcs.2021.06.005","volume":"880","author":"Y Zhu","year":"2021","unstructured":"Zhu Y, Pan X, Lv T, Liu Y, Li L (2021) DESN: an unsupervised MR image denoising network with deep image prior. Theor Comput Sci 880:97\u2013110. https:\/\/doi.org\/10.1016\/j.tcs.2021.06.005","journal-title":"Theor Comput Sci"},{"key":"3307_CR23","doi-asserted-by":"publisher","first-page":"12872","DOI":"10.1364\/OE.379200","volume":"28","author":"KC Zhou","year":"2020","unstructured":"Zhou KC, Horstmeyer R (2020) Diffraction tomography with a deep image prior. Opt Express 28:12872\u201312896. https:\/\/doi.org\/10.1364\/OE.379200","journal-title":"Opt Express"},{"key":"3307_CR24","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1016\/0168-9002(89)90802-4","volume":"277","author":"R Cesareo","year":"1989","unstructured":"Cesareo R, Mascarenhas S (1989) A new tomographic device based on the detection of fluorescent x-rays. Nucl Instrum Meth A 277:669\u2013672. https:\/\/doi.org\/10.1016\/0168-9002(89)90802-4","journal-title":"Nucl Instrum Meth A"},{"key":"3307_CR25","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1118\/1.595715","volume":"12","author":"RL Siddon","year":"1985","unstructured":"Siddon RL (1985) Fast calculation of the exact radiological path for a three-dimensional CT array. Med Phys 12:252\u2013255. https:\/\/doi.org\/10.1118\/1.595715","journal-title":"Med Phys"},{"key":"3307_CR26","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/42.363108","volume":"13","author":"HM Hudson","year":"1994","unstructured":"Hudson HM, Larkin RS (1994) Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging 13:601\u2013609. https:\/\/doi.org\/10.1109\/42.363108","journal-title":"IEEE Trans Med Imaging"},{"key":"3307_CR27","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1109\/TMI.1982.4307558","volume":"1","author":"LA Shepp","year":"1982","unstructured":"Shepp LA, Vardi Y (1982) Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imaging 1:113\u2013122. https:\/\/doi.org\/10.1109\/TMI.1982.4307558","journal-title":"IEEE Trans Med Imaging"},{"key":"3307_CR28","first-page":"306","volume":"8","author":"K Lange","year":"1984","unstructured":"Lange K, Carson R (1984) EM reconstruction algorithms for emission and transmission tomography. J Comput Assist Tomogr 8:306\u2013316","journal-title":"J Comput Assist Tomogr"},{"unstructured":"Ioffe S, Szegedy C (2015) Batch normalization: Accelerating deep network training by reducing internal covariate shift. In Proceedings of the 32nd International Conference on Machine Learning (ICML), Lille, France, pp 448\u2013456","key":"3307_CR29"},{"doi-asserted-by":"publisher","unstructured":"He K, Zhang X, Ren S, Sun J (2015) Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In: Proceedings of 2015 IEEE International Conference on Cumputer Vision (ICCV), Santiago, Chile, pp 1026\u20131034. https:\/\/doi.org\/10.1109\/ICCV.2015.123","key":"3307_CR30","DOI":"10.1109\/ICCV.2015.123"},{"key":"3307_CR31","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1021\/ac60259a007","volume":"40","author":"LA Currie","year":"1968","unstructured":"Currie LA (1968) Limits for qualitative detection and quantitative determination. Appl Radiochem Anal Chem 40:586\u2013593. https:\/\/doi.org\/10.1021\/ac60259a007","journal-title":"Appl Radiochem Anal Chem"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-024-03307-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11548-024-03307-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-024-03307-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,27]],"date-time":"2025-04-27T10:02:52Z","timestamp":1745748172000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11548-024-03307-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,29]]},"references-count":31,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["3307"],"URL":"https:\/\/doi.org\/10.1007\/s11548-024-03307-8","relation":{},"ISSN":["1861-6429"],"issn-type":[{"type":"electronic","value":"1861-6429"}],"subject":[],"published":{"date-parts":[[2024,12,29]]},"assertion":[{"value":"2 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 December 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"All animal experiments were approved by the Committee for Animal Research at Kyoto Pharmaceutical University.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"This article does not contain patient data.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}