{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:53:30Z","timestamp":1760147610642,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T00:00:00Z","timestamp":1676505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Materials"],"abstract":"<jats:p>In order to significantly reduce the computing time while, at the same time, keeping the accuracy and precision when determining the local values of the density and effective atomic number necessary for identifying various organic material, including explosives and narcotics, a specialized multi-stage procedure based on a multi-energy computed tomography investigation within the 20\u2013160 keV domain was elaborated. It consisted of a compensation for beam hardening and other non-linear effects that affect the energy dependency of the linear attenuation coefficient (LAC) in the chosen energy domain, followed by a 3D fast reconstruction algorithm capable of reconstructing the local LAC values for 64 energy values from 19.8 to 158.4 keV, and, finally, the creation of a set of algorithms permitting the simultaneous determination of the density and effective atomic number of the investigated materials. This enabled determining both the density and effective atomic number of complex objects in approximately 24 s, with an accuracy and precision of less than 3%, which is a significantly better performance with respect to the reported literature values.<\/jats:p>","DOI":"10.3390\/ma16041654","type":"journal-article","created":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T03:32:30Z","timestamp":1676518350000},"page":"1654","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Energy and Fast-Convergence Iterative Reconstruction Algorithm for Organic Material Identification Using X-ray Computed Tomography"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1583-7375","authenticated-orcid":false,"given":"Mihai","family":"Iovea","sequence":"first","affiliation":[{"name":"Accent Pro 2000 srl, 25A, M\u0103r\u0103\u0219e\u0219ti Str., 077125 Magurele (Ilfov), Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrei","family":"Stanciulescu","sequence":"additional","affiliation":[{"name":"Accent Pro 2000 srl, 25A, M\u0103r\u0103\u0219e\u0219ti Str., 077125 Magurele (Ilfov), Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edward","family":"Hermann","sequence":"additional","affiliation":[{"name":"Accent Pro 2000 srl, 25A, M\u0103r\u0103\u0219e\u0219ti Str., 077125 Magurele (Ilfov), Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marian","family":"Neagu","sequence":"additional","affiliation":[{"name":"Accent Pro 2000 srl, 25A, M\u0103r\u0103\u0219e\u0219ti Str., 077125 Magurele (Ilfov), Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4626-5920","authenticated-orcid":false,"given":"Octavian G.","family":"Duliu","sequence":"additional","affiliation":[{"name":"Accent Pro 2000 srl, 25A, M\u0103r\u0103\u0219e\u0219ti Str., 077125 Magurele (Ilfov), Romania"},{"name":"Department of Structure of Matter, Earth and Atmospheric Physics, Astrophysics, Faculty of Physics, University of Bucharest, 405, Atomistilor Str., 077125 Magurele (Ilfov), Romania"},{"name":"Geological Institute of Romania, 1, Caransebes Str., 012271 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"120372","DOI":"10.1016\/j.apenergy.2022.120372","article-title":"Thermotactic habit of gas hydrate growth enables a fast transformation of melting ice","volume":"331","author":"Yang","year":"2032","journal-title":"Appl. Energy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1038\/s41598-023-27409-6","article-title":"Monochromatic computed tomography using laboratory-scale setup","volume":"13","author":"Honkanen","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"16407","DOI":"10.1038\/s41598-022-20707-5","article-title":"Quantitative dual-energy CT as a nondestructive tool to identify indicators for fossilized bone in vertebrate paleontology","volume":"12","author":"Hamm","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1109\/TNS.2016.2514364","article-title":"System independent characterization of materials using dual-energy computed tomography","volume":"63","author":"Azevedo","year":"2016","journal-title":"IEEE Trans. Nucl. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1016\/j.combustflame.2020.12.025","article-title":"4D micro-scale, phase-contrast X-ray imaging and computed tomography of HMX-based polymer-bonded explosives during thermal runaway","volume":"226","author":"Parker","year":"2021","journal-title":"Combus. Flame"},{"key":"ref_6","unstructured":"Rebuffel, V., Rinkel, J., Tabary, J., and Verger, L. (2011, January 20\u201321). New perspectives of X-ray techniques for explosive detection based on CdTe\/CdZnTe spectrometric detectors. Proceedings of the International Symposium on Digital Industrial Radiology and Computed Tomography, Berlin, Germany. Available online: https:\/\/www.multixdetection.com\/article\/dir2011\/papers\/we21.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Eger, E., Do, S., Ishwar, P., Karl, W.C., and Pien, H. (2011, January 22\u201327). A learning-based approach to explosives detection using Multi-Energy X-ray Computed Tomography. Proceedings of the 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic.","DOI":"10.1109\/ICASSP.2011.5946904"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kaga, A., and Oxley, J.C. (2022). Counterterrorist Detection Techniques of Explosives, Elsevier. [2nd ed.]. Chapter 9.","DOI":"10.1016\/B978-0-444-64104-5.00012-6"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"87100W","DOI":"10.1117\/12.2017988","article-title":"Feasibility studies on explosive detection and homeland security applications using a neutron and X-ray combined computed tomography system","volume":"Volume 8710","author":"Fountain","year":"2013","journal-title":"Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.talanta.2012.09.055","article-title":"Standoff Raman spectrometry for the non-invasive detection of explosives precursors in highly fluorescing packaging","volume":"103","author":"Izake","year":"2013","journal-title":"Talanta"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Gudmundson, E., Jakobsson, A., and Stoica, P. (2009, January 9\u201310). NQR-based explosives detection\u2014An overview. Proceedings of the 2009 International Symposium on Signals, Circuits and Systems, Iasi, Romania.","DOI":"10.1109\/ISSCS.2009.5206220"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"Mrsf11-1405-y03-01","DOI":"10.1557\/opl.2012.19","article-title":"Remote Explosives Detection (RED) by infrared photothermal imaging","volume":"1405","author":"Kendziora","year":"2012","journal-title":"MRS Proc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/s13244-010-0057-0","article-title":"Dual- and multi-energy CT: Approach to functional imaging","volume":"2","author":"Fornaro","year":"2011","journal-title":"Insights Imaging"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3752","DOI":"10.1002\/mp.14241","article-title":"Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement","volume":"47","author":"Jacobsen","year":"2020","journal-title":"Med. Phys."},{"key":"ref_15","unstructured":"(2013). Engineering Aviation Security Environments\u2014Reduction of False Alarms in Computed Tomography- Based Screening of Checked Baggage, The National Academies Press."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"101","DOI":"10.4103\/1450-1147.203079","article-title":"Cadmium Telluride semiconductor detector for improved spatial and energy resolution radioisotopic imaging","volume":"16","author":"Abbaspour","year":"2017","journal-title":"World J. Nucl. Med."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Seller, P., Bell, S., Cernik, R., Christodoulou, C., Egan, C., Gaskin, J., Jacques, S., Pani, S., Ramsey, B., and Reid, C. (2021). Pixellated Cd(Zn)Te high-energy X-ray instrument. J. Instrument., 6.","DOI":"10.1088\/1748-0221\/6\/12\/C12009"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"102136","DOI":"10.1016\/j.ndteint.2019.102136","article-title":"Method for system-independent material characterization from spectral X-ray CT","volume":"107","author":"Busi","year":"2019","journal-title":"NDT E Int."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.clinimag.2020.07.030","article-title":"A comprehensive review of dual-energy and multi-spectral computed tomography","volume":"67","author":"Garnett","year":"2020","journal-title":"Clin. Imaging"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"229-1","DOI":"10.2352\/ISSN.2470-1173.2021.15.COIMG-229","article-title":"Enhanced material estimation with multi-spectral CT","volume":"I","author":"Devadithya","year":"2021","journal-title":"Electron. Imag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"102336","DOI":"10.1016\/j.ndteint.2020.102336","article-title":"System-independent material classification through X-ray attenuation","volume":"116","author":"Jumanazarov","year":"2020","journal-title":"NDT E Int."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"111864","DOI":"10.1016\/j.matchar.2022.111864","article-title":"Material classification from sparse spectral X-ray CT using vectorial total variation based on L infinity norm","volume":"187","author":"Jumanazarov","year":"2022","journal-title":"Mat. Character"},{"key":"ref_23","unstructured":"Clark, D.P., and Badea, C.T. (2018). Medical Imaging 2018: Physics of Medical Imaging, SPIE."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"043006","DOI":"10.1117\/1.JEI.27.4.043006","article-title":"Hybrid algorithm for few-views computed tomography of strongly absorbing media: Algebraic reconstruction, TV-regularization, and adaptive segmentation","volume":"27","author":"Vlasov","year":"2018","journal-title":"J. Electron. Imag."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1109\/TMM.2021.3070138","article-title":"Deep-IRTarget: An automatic target detector in infrared imagery using dual-domain feature extraction and allocation","volume":"24","author":"Zhang","year":"2022","journal-title":"IEEE Transact. Multimed."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.neucom.2021.10.110","article-title":"Graph-based few-shot learning with transformed feature propagation and optimal class allocation","volume":"470","author":"Zhang","year":"2022","journal-title":"Neurocomputing"},{"key":"ref_27","unstructured":"Zach, M., Kobler, E., and Pock, T. (2022). Computed Tomography reconstruction using generative energy-based priors. arXiv."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"094004","DOI":"10.1088\/1361-6420\/aba415","article-title":"Computed tomography reconstruction using deep image prior and learned reconstruction methods","volume":"36","author":"Baguer","year":"2020","journal-title":"Inverse Probl."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1088\/0031-9155\/21\/3\/004","article-title":"Beam hardening in X-ray reconstructive tomography","volume":"21","author":"Brooks","year":"1976","journal-title":"Phys. Med. Biol."},{"key":"ref_30","first-page":"9","article-title":"PAST: Paleontological Statistics Software Package for Education and Data Analysis","volume":"4","author":"Hammer","year":"2001","journal-title":"Palaeont. Electron."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"064001","DOI":"10.1088\/1361-6420\/aaba86","article-title":"Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography","volume":"34","author":"Kazantsev","year":"2018","journal-title":"Inverse Probl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1118\/1.595715","article-title":"Fast calculation of the exact radiological path for a three-dimensional CT array","volume":"12","author":"Siddon","year":"1985","journal-title":"Med. Phys."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"27","DOI":"10.5201\/ipol.2016.141","article-title":"On the implementation of collaborative TV regularization: Application to Cartoon+Texture decomposition","volume":"5","author":"Duran","year":"2016","journal-title":"Image Process. On-Line"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.phpro.2017.09.014","article-title":"Effective Atomic Number, Mass Attenuation Coefficient Parameterization, and Implications for High-Energy X-ray Cargo Inspection Systems","volume":"90","author":"Langeveld","year":"2017","journal-title":"Phys. Procedia"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"25129","DOI":"10.1364\/OE.24.025129","article-title":"Fast and Flexible X-ray Tomography Using the ASTRA Toolbox","volume":"24","author":"Palenstijn","year":"2016","journal-title":"Optics Express"}],"container-title":["Materials"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1996-1944\/16\/4\/1654\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:37:43Z","timestamp":1760121463000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1996-1944\/16\/4\/1654"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,16]]},"references-count":35,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["ma16041654"],"URL":"https:\/\/doi.org\/10.3390\/ma16041654","relation":{},"ISSN":["1996-1944"],"issn-type":[{"type":"electronic","value":"1996-1944"}],"subject":[],"published":{"date-parts":[[2023,2,16]]}}}