{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:13:22Z","timestamp":1792786402424,"version":"4.5.0"},"reference-count":45,"publisher":"International Union of Crystallography (IUCr)","issue":"5","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"The Defense Advanced Research Projects Agency","award":["HR00112520003"],"award-info":[{"award-number":["HR00112520003"]}],"id":[{"id":"https:\/\/ror.org\/02caytj08","id-type":"ROR","asserted-by":"crossref"}]},{"name":"NSF HAMMER-ERC","award":["EEC-2133630"],"award-info":[{"award-number":["EEC-2133630"]}]}],"content-domain":{"domain":["iucr.org","wiley.com","iucrj.org"],"crossmark-restriction":true},"short-container-title":["J Synchrotron Rad","J Synchrotron Radiat"],"accepted":{"date-parts":[[2026,7,28]]},"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:p>\n                    Full-field X-ray imaging techniques using laboratory-based and synchrotron sources are powerful and versatile tools used by academia and various industries to non-destructively characterize the internal structures of samples. In particular, synchrotron high-speed radiography and computed tomography (CT) have helped researchers address many critical problems by providing multiscale and multidimensional structural information. Owing to increased source brightness and improved spatial and temporal resolutions of modern detection systems, the generation rate of X-ray imaging data has accelerated dramatically in recent years. Consequently, manually analyzing the massive volume of X-ray image data has become a persistent bottleneck that hinders fast scientific discoveries and data-driven insights. To address this challenge, we developed\n                    <jats:italic>SMAXI<\/jats:italic>\n                    (\n                    <jats:italic>Software for Machine-Learning-assisted Analysis of X-ray Images<\/jats:italic>\n                    ), an open-source software designed for analyzing multidimensional full-field X-ray image data.\n                    <jats:italic>SMAXI<\/jats:italic>\n                    distinguishes itself from other conventional closed-source software by being fully customizable and open-source. It is GPU-accelerated and uses state-of-the art machine learning (ML) models to analyze time-resolved multidimensional X-ray imaging data.\n                    <jats:italic>SMAXI<\/jats:italic>\n                    's capabilities for image processing and analysis are demonstrated here using 2D static X-ray images, dynamic\n                    <jats:italic>in situ<\/jats:italic>\n                    X-ray videos, and complex volumetric CT data. By integrating advanced ML algorithms into a single customizable workflow,\n                    <jats:italic>SMAXI<\/jats:italic>\n                    can pre-process X-ray images using computer vision algorithms and automate object segmentation and tracking tasks, while utilizing a large language model-based chatbot for interactive geometry feature analysis. Ultimately,\n                    <jats:italic>SMAXI<\/jats:italic>\n                    will empower X-ray community members to overcome big-data limitations, accelerating the pace of scientific discovery that incorporates full-field X-ray imaging techniques.\n                  <\/jats:p>","DOI":"10.1107\/s1600577526007745","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T12:08:14Z","timestamp":1787573294000},"page":"1605-1617","update-policy":"https:\/\/doi.org\/10.1107\/cm_01","source":"Crossref","is-referenced-by-count":0,"title":["<i>SMAXI<\/i>\n                    : a machine-learning-powered open-source software for multidimensional full-field X-ray image analysis"],"prefix":"10.1107","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5665-8317","authenticated-orcid":true,"given":"Dukyong","family":"Kim","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/000e0be47","id-type":"ROR","asserted-by":"publisher"}],"department":["Department of Mechanical Engineering"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4881-9774","authenticated-orcid":true,"given":"Tao","family":"Sun","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/000e0be47","id-type":"ROR","asserted-by":"publisher"}],"department":["Department of Mechanical Engineering"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"329","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"tv5094_bb2","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1177\/0846537120941671","volume":"72","author":"Adams","year":"2021","journal-title":"Can. Assoc. Radiol. J."},{"key":"tv5094_bb18","unstructured":"Agiwal, H. & Pfefferkorn, F. E. (2025). Effect of Alloy Type on Material Flow Dynamics during Friction Stir Welding, Mendeley Data, https:\/\/doi.org\/10.17632\/hbz3k2fswn.1."},{"key":"tv5094_bb3","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1038\/s41586-024-07615-6","volume":"632","author":"Aidukas","year":"2024","journal-title":"Nature"},{"key":"tv5094_bb4","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","volume":"39","author":"Badrinarayanan","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"tv5094_bb5","first-page":"109531Z","volume":"10953","author":"Bullock","year":"2019","journal-title":"Proc. SPIE"},{"key":"tv5094_bb6","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.mattod.2019.08.011","volume":"34","author":"Cao","year":"2020","journal-title":"Mater. Today"},{"key":"tv5094_bb7","doi-asserted-by":"crossref","first-page":"87","DOI":"10.4316\/AECE.2013.01015","volume":"13","author":"Cernazanu-Glavan","year":"2013","journal-title":"Adv. Electr. Comput. Eng."},{"key":"tv5094_bb8","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.cjph.2020.01.010","volume":"65","author":"Chin","year":"2020","journal-title":"Chin. J. Phys."},{"key":"tv5094_bb9","doi-asserted-by":"crossref","first-page":"103119","DOI":"10.1063\/1.2857476","volume":"92","author":"Chu","year":"2008","journal-title":"Appl. Phys. Lett."},{"key":"tv5094_bb10","doi-asserted-by":"crossref","first-page":"100034","DOI":"10.1016\/j.ejrai.2025.100034","volume":"3","author":"Chukwujindu","year":"2025","journal-title":"Eur. J. Radiol. Artif. Intell."},{"key":"tv5094_bb11","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1126\/science.aav4687","volume":"363","author":"Cunningham","year":"2019","journal-title":"Science"},{"key":"tv5094_bb12","doi-asserted-by":"crossref","first-page":"034004","DOI":"10.1088\/1361-6501\/aa9c19","volume":"29","author":"De Carlo","year":"2018","journal-title":"Meas. Sci. Technol."},{"key":"tv5094_bb13","doi-asserted-by":"crossref","unstructured":"Dong, H., Gu, H., Chen, Y., Yang, J., Chen, Y. & Mazurowski, M. A. (2026). IEEE Trans. Biomed. Eng., https:\/\/doi.org\/10.1109\/TBME.2026.3653267.","DOI":"10.1109\/TBME.2026.3653267"},{"key":"tv5094_bb15","doi-asserted-by":"crossref","unstructured":"Ghoti, K., Baid, U. & Talbar, S. (2021). Proceedings of the 3rd International Conference on Advanced Technologies for Societal Applications (Techno-Societal 2020), pp. 519-531. Springer.","DOI":"10.1007\/978-3-030-69921-5_52"},{"key":"tv5094_bb16","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1107\/S1600577514013939","volume":"21","author":"G\u00fcrsoy","year":"2014","journal-title":"J. Synchrotron Rad."},{"key":"tv5094_bb17","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1109\/TBME.2025.3595981","volume":"73","author":"He","year":"2026","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"tv5094_bb19","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1038\/nature21698","volume":"543","author":"Holler","year":"2017","journal-title":"Nature"},{"key":"tv5094_bb20","unstructured":"Jalal, N. (2025). Heart Dataset Mendeley Data, V2, https:\/\/doi.org\/10.17632\/czmn5ypdz5.2."},{"key":"tv5094_bb21","doi-asserted-by":"crossref","first-page":"122805","DOI":"10.1109\/ACCESS.2024.3454188","volume":"12","author":"Khalili","year":"2024","journal-title":"IEEE Access"},{"key":"tv5094_bb14","unstructured":"Kim, D. (2026). SMAXI, https:\/\/github.com\/dukyong414\/SMAXI."},{"key":"tv5094_bb22","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., Doll\u00e1r, P. & Girshick, R. (2023). 2023 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW), pp. 4015-4026."},{"key":"tv5094_bb23","doi-asserted-by":"crossref","first-page":"103633","DOI":"10.1016\/j.micron.2024.103633","volume":"181","author":"Ko\u0161ek","year":"2024","journal-title":"Micron"},{"key":"tv5094_bb24","doi-asserted-by":"crossref","first-page":"e2325572","DOI":"10.1080\/17452759.2024.2325572","volume":"19","author":"Li","year":"2024","journal-title":"Virtual Physical Prototyping"},{"key":"tv5094_bb25","doi-asserted-by":"crossref","first-page":"e0257640","DOI":"10.1371\/journal.pone.0257640","volume":"16","author":"Li","year":"2021","journal-title":"PLoS One"},{"key":"tv5094_bb26","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1126\/science.aaf4914","volume":"353","author":"Lim","year":"2016","journal-title":"Science"},{"key":"tv5094_bb27","doi-asserted-by":"crossref","first-page":"104921","DOI":"10.1016\/j.addma.2025.104921","volume":"110","author":"Liu","year":"2025","journal-title":"Additive Manufacturing"},{"key":"tv5094_bb28","unstructured":"Ma, J., Yang, Z., Kim, S., Chen, B., Baharoon, M., Fallahpour, A., Asakereh, R., Lyu, H. & Wang, B. (2025). arXiv:2504.03600."},{"key":"tv5094_bb30","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1107\/S1600577522010311","volume":"30","author":"Nikitin","year":"2023","journal-title":"J. Synchrotron Rad."},{"key":"tv5094_bb29","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1107\/S1600577525007234","volume":"32","author":"Nikitin","year":"2025","journal-title":"J. Synchrotron Rad."},{"key":"tv5094_bb31","doi-asserted-by":"crossref","first-page":"20219892152","DOI":"10.34133\/2021\/9892152","volume":"2021","author":"Ou","year":"2021","journal-title":"Research"},{"key":"tv5094_bb32","doi-asserted-by":"crossref","unstructured":"Pandey, S., Chen, K.-F. & Dam, E. B. (2023). 2023 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW), pp. 2584-2590.","DOI":"10.1109\/ICCVW60793.2023.00273"},{"key":"tv5094_bb33","doi-asserted-by":"crossref","first-page":"2678","DOI":"10.1021\/nl200858y","volume":"11","author":"Rand","year":"2011","journal-title":"Nano Lett."},{"key":"tv5094_bb34","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P. & Brox, T. (2015). 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2015), pp. 234-241. Springer.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"tv5094_bb35","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.nima.2007.08.169","volume":"582","author":"Shen","year":"2007","journal-title":"Nucl. Instrum. Methods Phys. Res. A"},{"key":"tv5094_bb36","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1038\/s43246-024-00699-7","volume":"5","author":"Singh","year":"2024","journal-title":"Commun. Mater."},{"key":"tv5094_bb37","doi-asserted-by":"crossref","unstructured":"Sohan, M., Sai Ram, T. & Rami Reddy, C. V. (2024). ICDICI2024: International Conference Data Intelligence and Cognitive Informatics, pp. 529-545. Springer.","DOI":"10.1007\/978-981-99-7962-2_39"},{"key":"tv5094_bb1","unstructured":"Stannard, T., Williams, J., Singh, S., Singaravelu, A., Xiao, X. & Nikhilesh, C. (2017). Synchrotron X-ray Tomography for Three-Dimensional Time-Resolved Observations of Fatigue Crack Initiation and Growth from Corrosion Pits in Peak-Aged Al7075 Alloy Dataset, https:\/\/doi.org\/10.17038\/XSD\/1373575."},{"key":"tv5094_bb38","doi-asserted-by":"crossref","first-page":"110398","DOI":"10.1016\/j.istruc.2025.110398","volume":"81","author":"Sun","year":"2025","journal-title":"Structures"},{"key":"tv5094_bb39","doi-asserted-by":"crossref","unstructured":"Takeuchi, A., Uesugi, M., Uesugi, K. & Tsuritani, H. (2023). AIP Conf. Proc. 2990, 040012.","DOI":"10.1063\/5.0168573"},{"key":"tv5094_bb40","unstructured":"Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozi\u00e8re, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E. & Lample, G. (2023). arXiv:2302.13971."},{"key":"tv5094_bb41","doi-asserted-by":"crossref","first-page":"1802291","DOI":"10.1002\/smll.201802291","volume":"14","author":"Wang","year":"2018","journal-title":"Small"},{"key":"tv5094_bb42","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s40510-023-00465-4","volume":"24","author":"Yang","year":"2023","journal-title":"Prog. Orthod."},{"key":"tv5094_bb43","unstructured":"Zhang, C., Liu, L., Cui, Y., Huang, G., Lin, W., Yang, Y. & Hu, Y. (2023). arXiv:2305.08196."},{"key":"tv5094_bb44","doi-asserted-by":"crossref","first-page":"108238","DOI":"10.1016\/j.compbiomed.2024.108238","volume":"171","author":"Zhang","year":"2024","journal-title":"Comput. Biol. Med."},{"key":"tv5094_bb45","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1126\/science.abd1587","volume":"370","author":"Zhao","year":"2020","journal-title":"Science"}],"container-title":["Journal of Synchrotron Radiation"],"original-title":[],"link":[{"URL":"https:\/\/journals.iucr.org\/s\/issues\/2026\/05\/00\/tv5094\/tv5094.pdf","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.iucr.org\/s\/issues\/2026\/05\/00\/tv5094\/tv5094.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T11:04:44Z","timestamp":1790939084000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.iucr.org\/paper?S1600577526007745"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,26]]},"references-count":45,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["S1600577526007745"],"URL":"https:\/\/doi.org\/10.1107\/s1600577526007745","relation":{"is-supplemented-by":[{"id-type":"doi","id":"10.1107\/S1600577526007745\/tv5094sup1.mp4","asserted-by":"subject"},{"id-type":"doi","id":"10.1107\/S1600577526007745\/tv5094sup2.mp4","asserted-by":"subject"}]},"ISSN":["1600-5775"],"issn-type":[{"value":"1600-5775","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,26]]},"assertion":[{"value":"Journal of Synchrotron Radiation","order":0,"name":"journal","label":"Publication","explanation":{"URL":"https:\/\/journals.iucr.org\/s"},"group":{"name":"general","label":"General"}},{"value":"computer programs","order":1,"name":"content_type","label":"Content type","explanation":{"URL":"https:\/\/journals.iucr.org\/s\/services\/notesforauthors.html"},"group":{"name":"general","label":"General"}},{"value":"Available","URL":"https:\/\/scripts.iucr.org\/cgi-bin\/citedin?tv5094","order":2,"name":"article_metrics","label":"Article metrics","group":{"name":"general","label":"General"}},{"value":"Yes","order":0,"name":"peer_reviewed","label":"Peer reviewed","group":{"name":"peer_review","label":"Peer review"}},{"value":"Single blind","order":1,"name":"review_process","label":"Review process","group":{"name":"peer_review","label":"Peer review"}},{"value":"4 June 2026","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication history"}},{"value":"28 July 2026","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication history"}},{"value":"26 August 2026","order":2,"name":"published_online","label":"Published online","group":{"name":"publication_history","label":"Publication history"}},{"value":"This article has supporting information","name":"supplementary_materials","label":"Supplementary materials","explanation":{"URL":"https:\/\/scripts.iucr.org\/cgi-bin\/sendsup?tv5094"}},{"value":"\u00a9 2026 Dukyong Kim and Tao Sun","order":0,"name":"copyright","label":"Copyright","explanation":{"URL":"https:\/\/journals.iucr.org\/services\/copyrightpolicy.html"},"group":{"name":"copyright_and_licencing","label":"Copyright and licencing"}},{"value":"Creative Commons Attribution (CC-BY)","order":1,"name":"license","label":"Licence","explanation":{"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},"group":{"name":"copyright_and_licencing","label":"Copyright and licencing"}}]}}