{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T09:57:30Z","timestamp":1791021450140,"version":"4.1.0"},"reference-count":95,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:00:00Z","timestamp":1790985600000},"content-version":"vor","delay-in-days":275,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100006319","name":"Centre National pour la Recherche Scientifique et Technique","doi-asserted-by":"publisher","award":["UH192022"],"award-info":[{"award-number":["UH192022"]}],"id":[{"id":"10.13039\/501100006319","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Biomedical Imaging"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:p>Ultrasound imaging is a widely used diagnostic tool, and beamforming techniques are integral to its performance. Traditional methods such as delay\u2010and\u2010sum (DAS) and delay\u2010multiply\u2010and sum (DMAS) have limitations in terms of image quality and computational efficiency. Recently, deep learning approaches have shown significant promise in improving ultrasound beamforming, offering enhanced image resolution and quality, alongside potential for real\u2010time processing. This review is aimed at providing a comprehensive overview of the current state\u2010of\u2010the\u2010art in deep learning\u2013based ultrasound beamforming. It focuses on analyzing various deep learning models, their applications, challenges, and the integration of hardware optimization strategies to enhance performance and efficiency. The review examines a range of deep learning models applied to ultrasound beamforming, including convolutional neural networks (CNNs), generative adversarial networks (GANs), transformer\u2010based models, and hybrid approaches. It also discusses the challenges associated with dataset limitations, model interpretability, and the risk of overfitting. Furthermore, the review explores hardware acceleration using field\u2010programmable gate arrays (FPGAs), along with cloud\u2010edge frameworks for real\u2010time inference. The findings highlight the potential of deep learning models to outperform traditional methods in terms of image quality and resolution. However, challenges such as the need for large and diverse datasets, the black box nature of deep learning models, and the risk of overfitting remain. Hardware optimization through FPGAs has proven effective in enabling real\u2010time processing, but the integration of edge computing with cloud\u2010based solutions offers promising avenues for balancing performance, latency, and energy efficiency. Deep learning\u2013based ultrasound beamforming has great potential to advance medical imaging. Future efforts should enhance model generalizability with diverse and synthetic data, optimize hardware for real\u2010time use, and establish standardized validation protocols to support clinical adoption.<\/jats:p>","DOI":"10.1155\/ijbi\/4617573","type":"journal-article","created":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T09:35:07Z","timestamp":1791020107000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Advancing Ultrasound Beamforming With Deep Learning: A Comprehensive Review of Methods, Datasets, Benchmarks, and Computational Challenges"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7204-0421","authenticated-orcid":false,"given":"Hamza","family":"Hadri","sequence":"first","affiliation":[{"name":"NEST Research Group LESE Lab ENSEM of Hassan II University of Casablanca  Casablanca Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abderahhim","family":"Fail","sequence":"additional","affiliation":[{"name":"NEST Research Group LESE Lab ENSEM of Hassan II University of Casablanca  Casablanca Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Sadik","sequence":"additional","affiliation":[{"name":"IESI Laboratory of ENSET Mohammedia Hassan II University of Casablanca  Casablanca Morocco  uh2c.ac.ma"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,3]]},"reference":[{"key":"e_1_2_13_1_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447243"},{"key":"e_1_2_13_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/fphy.2020.00124"},{"key":"e_1_2_13_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcmg.2019.09.019"},{"key":"e_1_2_13_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2022.11.003"},{"key":"e_1_2_13_5_2","first-page":"88","volume-title":"International Conference on Advanced Intelligent Systems for Sustainable Development","author":"Hadri H.","year":"2024"},{"key":"e_1_2_13_6_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-50317-7"},{"key":"e_1_2_13_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2019.11.013"},{"key":"e_1_2_13_8_2","volume-title":"Proceedings of the 2nd International Conference on Advanced Technologies for Humanity (Vol. 1, pp. 103-109)","author":"Dangoury S.","year":"2020"},{"key":"e_1_2_13_9_2","first-page":"107221","volume-title":"Comment on \u201cSo You Think You Can DAS? A Viewpoint on Delay-and-Sum Beamforming\u201d","author":"Schiffner M. F.","year":"2023"},{"key":"e_1_2_13_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.104807"},{"key":"e_1_2_13_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2022.106838"},{"key":"e_1_2_13_12_2","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/abef45","article-title":"Super-Resolution Ultrasound Localization Microscopy Based on a High Frame-Rate Clinical Ultrasound Scanner: An In-Human Feasibility Study","volume":"66","author":"Huang C.","year":"2021","journal-title":"Physics in Medicine & Biology"},{"key":"e_1_2_13_13_2","doi-asserted-by":"publisher","DOI":"10.1177\/01617346231163835"},{"key":"e_1_2_13_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2022.01.009"},{"key":"e_1_2_13_15_2","doi-asserted-by":"publisher","DOI":"10.3389\/fphy.2024.1398393"},{"key":"e_1_2_13_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2021.3126578"},{"key":"e_1_2_13_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBCAS.2023.3267614"},{"key":"e_1_2_13_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2021.3094849"},{"key":"e_1_2_13_19_2","unstructured":"SimonyanK.andZissermanA. Very Deep Convolutional Networks for Large-Scale Image Recognition 2014 Preprint arXiv preprint arXiv:1409.1556 September 4 2014https:\/\/doi.org\/10.48550\/arXiv.1409.1556."},{"key":"e_1_2_13_20_2","unstructured":"HowardA. G. Mobilenets: Efficient Convolutional Neural Networks for Mobile Vision Applications Preprint arXiv preprint arXiv:1704.04861 April 17 2017."},{"key":"e_1_2_13_21_2","doi-asserted-by":"publisher","DOI":"10.3390\/app12136562"},{"key":"e_1_2_13_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ndteint.2021.102575"},{"key":"e_1_2_13_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinane.2022.110666"},{"key":"e_1_2_13_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2371235"},{"key":"e_1_2_13_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2017.2690959"},{"key":"e_1_2_13_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2022.106864"},{"key":"e_1_2_13_27_2","doi-asserted-by":"publisher","DOI":"10.32604\/cmes.2021.016008"},{"key":"e_1_2_13_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3195299"},{"key":"e_1_2_13_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3071301"},{"key":"e_1_2_13_30_2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics14151669"},{"key":"e_1_2_13_31_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2809641"},{"key":"e_1_2_13_32_2","first-page":"1","volume-title":"In 2018 IEEE International Ultrasonics Symposium (IUS)","author":"Simson W.","year":"2018"},{"key":"e_1_2_13_33_2","first-page":"619","volume-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","author":"Khan S.","year":"2019"},{"key":"e_1_2_13_34_2","first-page":"717","volume-title":"In 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","author":"Fouad M.","year":"2020"},{"key":"e_1_2_13_35_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Rothl\u00fcbbers S.","year":"2020"},{"key":"e_1_2_13_36_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Goudarzi S.","year":"2020"},{"key":"e_1_2_13_37_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2022.106823"},{"key":"e_1_2_13_38_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Perdios D.","year":"2020"},{"key":"e_1_2_13_39_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2022.102073"},{"key":"e_1_2_13_40_2","doi-asserted-by":"publisher","DOI":"10.1121\/10.0021171"},{"key":"e_1_2_13_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2022.3160859"},{"key":"e_1_2_13_42_2","doi-asserted-by":"publisher","DOI":"10.3390\/s24165111"},{"key":"e_1_2_13_43_2","doi-asserted-by":"publisher","DOI":"10.3390\/info14100582"},{"key":"e_1_2_13_44_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2022.106778"},{"key":"e_1_2_13_45_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107384"},{"key":"e_1_2_13_46_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102086"},{"key":"e_1_2_13_47_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Khan S.","year":"2020"},{"key":"e_1_2_13_48_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2024.107408"},{"key":"e_1_2_13_49_2","first-page":"1","volume-title":"In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE)","author":"Rahoof A.","year":"2024"},{"key":"e_1_2_13_50_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2022.106833"},{"key":"e_1_2_13_51_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2023.106981"},{"key":"e_1_2_13_52_2","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"e_1_2_13_53_2","doi-asserted-by":"publisher","DOI":"10.1002\/mp.17948"},{"key":"e_1_2_13_54_2","first-page":"1","volume-title":"In 2018 IEEE International Ultrasonics Symposium (IUS)","author":"Nair A. A.","year":"2018"},{"key":"e_1_2_13_55_2","volume-title":"In Medical Image Com-Puting and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18 (pp. 234-241)","author":"Ronneberger O.","year":"2015"},{"key":"e_1_2_13_56_2","first-page":"636","volume-title":"In 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821)","author":"Jensen J. A.","year":"2004"},{"key":"e_1_2_13_57_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Zhang J.","year":"2020"},{"key":"e_1_2_13_58_2","doi-asserted-by":"crossref","unstructured":"ChenY. LiuJ. LuoX.et al. A Self-Supervised Deep Learning Approach for High Frame Rate Plane Wave Beamforming with Two-Way Dynamic Focusing 2021 IEEE International Ultrasonics Symposium (IUS) 2021 1\u20134.","DOI":"10.1109\/IUS52206.2021.9593334"},{"key":"e_1_2_13_59_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Bell M. A. L.","year":"2020"},{"key":"e_1_2_13_60_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Wang Y.","year":"2020"},{"key":"e_1_2_13_61_2","first-page":"1","volume-title":"In 2020 IEEE International Ultrasonics Symposium (IUS)","author":"Li Z.","year":"2020"},{"key":"e_1_2_13_62_2","doi-asserted-by":"publisher","DOI":"10.1109\/58.139123"},{"key":"e_1_2_13_63_2","doi-asserted-by":"publisher","DOI":"10.3390\/s16111873"},{"key":"e_1_2_13_64_2","first-page":"1","volume-title":"In 2022 IEEE International Ultrasonics Symposium (IUS)","author":"Zhang J.","year":"2022"},{"key":"e_1_2_13_65_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2024.107562"},{"key":"e_1_2_13_66_2","first-page":"1","volume-title":"In 2017 IEEE International Ultrasonics Symposium (IUS)","author":"Rodriguez-Molares A.","year":"2017"},{"key":"e_1_2_13_67_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.3360308"},{"key":"e_1_2_13_68_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2015.10.020"},{"key":"e_1_2_13_69_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2025.108620"},{"key":"e_1_2_13_70_2","first-page":"1","volume-title":"Oceans 2022","author":"Menakath M. M.","year":"2022"},{"key":"e_1_2_13_71_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijtm4010011"},{"key":"e_1_2_13_72_2","volume-title":"Introduction to COMSOL Multiphysics","author":"Multiphysics, COMSOL","year":"1998"},{"key":"e_1_2_13_73_2","first-page":"1","volume-title":"In 2016 IEEE International ultrasonics symposium (IUS)","author":"Liebgott H.","year":"2016"},{"key":"e_1_2_13_74_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3087819"},{"key":"e_1_2_13_75_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103446"},{"key":"e_1_2_13_76_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2018.2883427"},{"key":"e_1_2_13_77_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2017.05.023"},{"key":"e_1_2_13_78_2","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.12544"},{"key":"e_1_2_13_79_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2021.3055498"},{"key":"e_1_2_13_80_2","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2022.880966"},{"key":"e_1_2_13_81_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2019.2956855"},{"key":"e_1_2_13_82_2","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2023.3289157"},{"key":"e_1_2_13_83_2","doi-asserted-by":"crossref","DOI":"10.1016\/j.ultras.2024.107562","article-title":"Overfit Detection Method for Deep Neural Networks Trained to Beamform Ultrasound Images","volume":"148","author":"Zhang J.","year":"2025","journal-title":"Ultrasonics"},{"key":"e_1_2_13_84_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3330229"},{"key":"e_1_2_13_85_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102444"},{"key":"e_1_2_13_86_2","doi-asserted-by":"publisher","DOI":"10.1145\/3510413"},{"key":"e_1_2_13_87_2","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1007\/978-3-031-37703-7_21","volume-title":"International Conference on Computer Aided Verification","author":"Amir G.","year":"2023"},{"key":"e_1_2_13_88_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613963"},{"key":"e_1_2_13_89_2","unstructured":"JunX. FPGA Deep Learning Acceleration Based on Convolutional Neural Network Preprint arXiv preprint arXiv:2012.03672 November 17 2020."},{"key":"e_1_2_13_90_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3761-1"},{"key":"e_1_2_13_91_2","doi-asserted-by":"publisher","DOI":"10.1080\/2374068X.2021.1909332"},{"key":"e_1_2_13_92_2","doi-asserted-by":"publisher","DOI":"10.3390\/ai6060124"},{"key":"e_1_2_13_93_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ndteint.2009.10.001"},{"key":"e_1_2_13_94_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2023.107085"},{"key":"e_1_2_13_95_2","first-page":"1339","volume-title":"In 2024 4th International Conference on Technological Advancements in Computational Sciences (ICTACS)","author":"Hadri H.","year":"2024"}],"container-title":["International Journal of Biomedical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/ijbi\/4617573","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1155\/ijbi\/4617573","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/ijbi\/4617573","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T09:35:18Z","timestamp":1791020118000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/ijbi\/4617573"}},"subtitle":[],"editor":[{"given":"Sohini","family":"Basu Roy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":95,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1155\/ijbi\/4617573"],"URL":"https:\/\/doi.org\/10.1155\/ijbi\/4617573","archive":["Portico"],"relation":{},"ISSN":["1687-4188","1687-4196"],"issn-type":[{"value":"1687-4188","type":"print"},{"value":"1687-4196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2025-05-12","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-12","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-10-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"4617573"}}