{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T14:35:08Z","timestamp":1785335708307,"version":"3.55.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T00:00:00Z","timestamp":1752019200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T00:00:00Z","timestamp":1752019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s11760-025-04452-6","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T09:43:00Z","timestamp":1752140580000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deformation field prediction based on a modified loss function with U-Net for non rigid image registration"],"prefix":"10.1007","volume":"19","author":[{"given":"Omaima","family":"El Bahi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youssef","family":"Qaraai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmad","family":"El Allaoui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"key":"4452_CR1","doi-asserted-by":"crossref","unstructured":"Tondewad, M. P. S. & Dale, M. M. P.: Remote sensing image registration methodology: review and discussion. Procedia Comput Sci. 171, 2390\u20132399 (2020).","DOI":"10.1016\/j.procs.2020.04.259"},{"key":"4452_CR2","doi-asserted-by":"publisher","first-page":"106767","DOI":"10.1016\/j.compeleceng.2020.106767","volume":"87","author":"HR Boveiri","year":"2020","unstructured":"Boveiri, H.R., Khayami, R., Javidan, R., Mehdizadeh, A.: Medical image registration using deep neural networks: a comprehensive review. Comput. Electr. Eng. 87, 106767 (2020)","journal-title":"Comput. Electr. Eng."},{"key":"4452_CR3","unstructured":"Modality-agnostic structural image representation learning for deformable multi-modality medical image registration. arXiv.org abs\/2402.18933, (2024)."},{"key":"4452_CR4","first-page":"344","volume":"10433 LNCS","author":"J Krebs","year":"2017","unstructured":"Krebs, J., et al.: Robust non-rigid registration through agent-based action learning. Lecture Notes Comput. Sci. (including Subser. Lecture Notes Artif. Intell. Lecture Notes Bioinformatics). 10433 LNCS, 344\u2013352 (2017)","journal-title":"Lecture Notes Comput. Sci. (including Subser. Lecture Notes Artif. Intell. Lecture Notes Bioinformatics)"},{"key":"4452_CR5","doi-asserted-by":"crossref","unstructured":"Yang, F., Ding, M. & Zhang, X.: Non-rigid multi-modal 3D medical image registration based on foveated modality independent neighborhood descriptor. Sensors. 19, 4675 (2019).","DOI":"10.3390\/s19214675"},{"key":"4452_CR6","doi-asserted-by":"publisher","unstructured":"Andrade, N., Faria, F. A. & Cappabianco, F. A. M.: A practical review on medical image registration: from rigid to deep learning based approaches. Proceedings\u2013\u200931stConferenceonGraphics,PatternsandImages,SIBGRAPI. 2018, 463\u2013470 (2018). https:\/\/doi.org\/10.1109\/SIBGRAPI.2018.00066.","DOI":"10.1109\/SIBGRAPI.2018.00066"},{"key":"4452_CR7","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1007\/s10278-016-9915-8","volume":"30","author":"AP Keszei","year":"2017","unstructured":"Keszei, A.P., Berkels, B., Deserno, T.M.: Survey of non-rigid registration tools in medicine. J. Digit. Imaging. 30, 102\u2013116 (2017)","journal-title":"J. Digit. Imaging"},{"key":"4452_CR8","unstructured":"Zhang UCLA, X., Dong, H., Gao, D. & Zhao UCLA, X.: A comparative study for non-rigid image registration and rigid image registration *."},{"key":"4452_CR9","unstructured":"Markov Random Field Modeling in Computer Vision - S.Z. Li - Google Livres. https:\/\/books.google.co.ma\/books."},{"key":"4452_CR10","doi-asserted-by":"publisher","first-page":"1788","DOI":"10.1109\/TMI.2019.2897538","volume":"38","author":"G Balakrishnan","year":"2019","unstructured":"Balakrishnan, G., Zhao, A., Sabuncu, M.R., Guttag, J., Dalca, A.V.: VoxelMorph: a learning framework for deformable medical image registration. IEEE Trans. Med. Imaging. 38, 1788\u20131800 (2019)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"4452_CR11","doi-asserted-by":"crossref","unstructured":"Pei, Y. etal.: Non-rigid craniofacial 2D-3D registration using CNN-based regression. LectureNotesinComputerScience(includingsubseriesLectureNotesinArtificialIntelligenceandLectureNotesinBioinformatics). 10553 LNCS, 117\u2013125 (2017).","DOI":"10.1007\/978-3-319-67558-9_14"},{"key":"4452_CR12","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1007\/978-3-031-48465-0_69","volume":"837 LNNS","author":"O El Bahi","year":"2024","unstructured":"El Bahi, O., Alaoui, A.O., Qaraai, Y., El Allaoui, A.: Deep feature-based matching of high-resolution multitemporal images using VGG16 and VGG19 algorithms. Lecture Notes Networks Syst. 837 LNNS, 516\u2013521 (2024)","journal-title":"Lecture Notes Networks Syst."},{"key":"4452_CR13","first-page":"16","volume":"1","author":"C Hernandez-Matas","year":"2017","unstructured":"Hernandez-Matas, C., et al.: FIRE: fundus image registration dataset. Model. Artif. Intell. Ophthalmol. 1, 16\u201328 (2017)","journal-title":"Model. Artif. Intell. Ophthalmol."},{"key":"4452_CR14","doi-asserted-by":"crossref","unstructured":"Jiang, Z., Ding, C., Liu, M. & Tao, D.: Two-stage cascaded U-Net: 1st place solution to BraTS challenge 2019 segmentation task. LectureNotesinComputerScience(includingsubseriesLectureNotesinArtificialIntelligenceandLectureNotesinBioinformatics). 11992 LNCS, 231\u2013241 (2020).","DOI":"10.1007\/978-3-030-46640-4_22"},{"key":"4452_CR15","doi-asserted-by":"crossref","unstructured":"Chen, H. & Shi, Z.: A spatial-temporal attention-based method and a new dataset for remote sensing image change detection. Remote Sensing. 12, 1662 (2020).","DOI":"10.3390\/rs12101662"},{"key":"4452_CR16","doi-asserted-by":"crossref","unstructured":"Sara, U. etal.: Image quality assessment through FSIM, SSIM, MSE and PSNR\u2014a comparative study. Journal of Computer and Communications. 7, 8\u201318 (2019).","DOI":"10.4236\/jcc.2019.73002"},{"key":"4452_CR17","unstructured":"Bharati, S., Mondal, M. R. H., Podder, P. & Prasath, V. B. S.: Deep learning for medical image registration: a comprehensive review. International Journal of Computer Information Systems and Industrial Management Applications. 14, 173\u2013190 (2022)."},{"key":"4452_CR18","doi-asserted-by":"crossref","unstructured":"Li, H. & Fan, Y.: Non-rigid image registration using self-supervised fully convolutional networks without training data. Proceedings-InternationalSymposiumonBiomedicalImaging. 2018-April, 1075\u20131078 (2018).","DOI":"10.1109\/ISBI.2018.8363757"},{"key":"4452_CR19","doi-asserted-by":"crossref","unstructured":"Benvenuto, G. A. etal.: A fully unsupervised deep learning framework for non-rigid fundus image registration. Bioengineering. 9, 369 (2022).","DOI":"10.3390\/bioengineering9080369"},{"key":"4452_CR20","doi-asserted-by":"crossref","unstructured":"Krebs, J., Delingette, H., Mailhe, B., Ayache, N. & Mansi, T.: Learning a probabilistic model for diffeomorphic registration. IEEE Trans Med Imaging. 38, 2165\u20132176 (2019).","DOI":"10.1109\/TMI.2019.2897112"},{"key":"4452_CR21","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s11548-021-02511-0","volume":"17","author":"S Shao","year":"2022","unstructured":"Shao, S., et al.: A multi-scale unsupervised learning for deformable image registration. Int. J. Comput. Assist. Radiol. Surg. 17, 157\u2013166 (2022)","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"4452_CR22","doi-asserted-by":"publisher","first-page":"4895","DOI":"10.21037\/qims-21-175","volume":"11","author":"H Xiao","year":"2021","unstructured":"Xiao, H., et al.: A review of deep learning-based three-dimensional medical image registration methods. Quant. Imaging Med. Surg. 11, 4895 (2021)","journal-title":"Quant. Imaging Med. Surg."},{"key":"4452_CR23","doi-asserted-by":"crossref","unstructured":"Jaganathan, S., Wang, J., Borsdorf, A., Shetty, K. & Maier, A.: Deep iterative 2D\/3D registration. LectureNotesinComputerScience(includingsubseriesLectureNotesinArtificialIntelligenceandLectureNotesinBioinformatics). 12904 LNCS, 383\u2013392 (2021).","DOI":"10.1007\/978-3-030-87202-1_37"},{"key":"4452_CR24","doi-asserted-by":"crossref","unstructured":"Upendra, R. R., Simon, R., Shontz, S. M. & Linte, C. A.: Deformable image registration using vision transformers for cardiac motion estimation from cine cardiac MRI images. LectureNotesinComputerScience(includingsubseriesLectureNotesinArtificialIntelligenceandLectureNotesinBioinformatics). 13958 LNCS, 375\u2013383 (2023).","DOI":"10.1007\/978-3-031-35302-4_39"},{"key":"4452_CR25","unstructured":"Mok, T. C. W. & Chung, A. C. S.: Affine medical image registration with coarse-to-fine vision transformer. 20835\u201320844 Preprint at https:\/\/github.com\/cwmok\/C2FViT. (2022)."},{"key":"4452_CR26","doi-asserted-by":"publisher","first-page":"102383","DOI":"10.1016\/j.media.2022.102383","volume":"78","author":"M Sinclair","year":"2022","unstructured":"Sinclair, M., et al.: Atlas-ISTN: joint segmentation, registration and atlas construction with image-and-spatial transformer networks. Med. Image Anal. 78, 102383 (2022)","journal-title":"Med. Image Anal."},{"key":"4452_CR27","doi-asserted-by":"publisher","unstructured":"Wang, Y., Yu, Q. & Yu, W.: An improved normalized cross correlation algorithm for SAR image registration. InternationalGeoscienceandRemoteSensingSymposium(IGARSS). 2086\u20132089 (2012). https:\/\/doi.org\/10.1109\/IGARSS.2012.6350961.","DOI":"10.1109\/IGARSS.2012.6350961"},{"key":"4452_CR28","doi-asserted-by":"crossref","unstructured":"Hager, G. D., Dewan, M. & Stewart, C. V.: Multiple kernel tracking with SSD. ProceedingsoftheIEEEComputerSocietyConferenceonComputerVisionandPatternRecognition. 1, (2004).","DOI":"10.1109\/CVPR.2004.1315112"},{"key":"4452_CR29","doi-asserted-by":"crossref","unstructured":"Mahapatra, D., Antony, B., Sedai, S. & Garnavi, R.: Deformable medical image registration using generative adversarial networks. Proceedings-InternationalSymposiumonBiomedicalImaging 2018-April, 1449\u20131453 (2018).","DOI":"10.1109\/ISBI.2018.8363845"},{"key":"4452_CR30","unstructured":"Kori, A. & Krishnamurthi, G.: Zero shot learning for multi-modal real time image registration. (2019)."},{"key":"4452_CR31","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1016\/j.compeleceng.2016.11.034","volume":"62","author":"Z Hossein-Nejad","year":"2017","unstructured":"Hossein-Nejad, Z., Nasri, M.: An adaptive image registration method based on SIFT features and RANSAC transform. Comput. Electr. Eng. 62, 524\u2013537 (2017)","journal-title":"Comput. Electr. Eng."},{"key":"4452_CR32","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1007\/978-3-319-59057-8_9","volume":"199","author":"V Popovic","year":"2017","unstructured":"Popovic, V., Seyid, K., Cogal, \u00d6., Akin, A., Leblebici, Y.: Real-Time image registration via optical flow calculation. Des. Implement. Real-time multi-sensor Vis. Syst. 199, 224 (2017). https:\/\/doi.org\/10.1007\/978-3-319-59057-8_9.","journal-title":"Des. Implement. Real-Time Multi-Sensor Vis. Syst."},{"key":"4452_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v086.i08","volume":"86","author":"R Beare","year":"2018","unstructured":"Beare, R., Lowekamp, B., Yaniv, Z.: Image segmentation, registration and characterization in R with simpleitk. J. Stat. Softw. 86, 1\u201335 (2018)","journal-title":"J. Stat. Softw."},{"key":"4452_CR34","doi-asserted-by":"crossref","unstructured":"de Vos, B. D., Berendsen, F. F., Viergever, M. A., Staring, M. & I\u0161gum, I.: End-to-end unsupervised deformable image registration with a convolutional neural network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10553 LNCS, 204\u2013212 (2017).","DOI":"10.1007\/978-3-319-67558-9_24"},{"key":"4452_CR35","unstructured":"Durech, E. F.: Deep convolutional neural network for non-rigid image registration. (2021)."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04452-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04452-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04452-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T03:26:45Z","timestamp":1757215605000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04452-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,9]]},"references-count":35,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["4452"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04452-6","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,9]]},"assertion":[{"value":"6 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 June 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2025","order":4,"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 no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"857"}}