{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T08:39:40Z","timestamp":1793176780545,"version":"4.5.0"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T00:00:00Z","timestamp":1784937600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Photoacoustics"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.pacs.2026.100863","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T15:24:57Z","timestamp":1785770697000},"page":"100863","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Real-time deep learning-based vascular recognition in clinical breast photoacoustic imaging"],"prefix":"10.1016","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3639-5158","authenticated-orcid":false,"given":"Wenhan","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1206-1983","authenticated-orcid":false,"given":"Zeyang","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keer","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenzhong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxiao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunrui","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingjun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.pacs.2026.100863_b1","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.breast.2022.08.010","article-title":"Current and future burden of breast cancer: Global statistics for 2020 and 2040","volume":"66","author":"Arnold","year":"2022","journal-title":"Breast"},{"issue":"3","key":"10.1016\/j.pacs.2026.100863_b2","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. Clin."},{"issue":"1","key":"10.1016\/j.pacs.2026.100863_b3","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1186\/s13058-015-0525-z","article-title":"Benefits and harms of mammography screening","volume":"17","author":"L\u00f8berg","year":"2015","journal-title":"Breast Cancer Res."},{"issue":"9310","key":"10.1016\/j.pacs.2026.100863_b4","doi-asserted-by":"crossref","first-page":"909","DOI":"10.1016\/S0140-6736(02)08020-0","article-title":"Long-term effects of mammography screening: Updated overview of the Swedish randomised trials","volume":"359","author":"Nystr\u00f6m","year":"2002","journal-title":"Lancet"},{"issue":"1\u20133","key":"10.1016\/j.pacs.2026.100863_b5","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.pbiomolbio.2006.07.010","article-title":"Ultrasound\u2013biophysics mechanisms","volume":"93","author":"O\u2019Brien","year":"2007","journal-title":"Prog. Biophys. Mol. Biol."},{"issue":"18","key":"10.1016\/j.pacs.2026.100863_b6","doi-asserted-by":"crossref","first-page":"2151","DOI":"10.1001\/jama.299.18.2151","article-title":"Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer","volume":"299","author":"Berg","year":"2008","journal-title":"JAMA"},{"issue":"2","key":"10.1016\/j.pacs.2026.100863_b7","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2214\/AJR.13.12072","article-title":"Screening breast ultrasound: Past, present, and future","volume":"204","author":"Brem","year":"2015","journal-title":"Am. J. Roentgenol."},{"key":"10.1016\/j.pacs.2026.100863_b8","doi-asserted-by":"crossref","first-page":"53","DOI":"10.4137\/BCBCR.S38432","article-title":"A retrospective study evaluating the impact of preoperative breast mri on surgical decision-making in young patients (\u226450 years) with invasive breast cancer","volume":"10","author":"Mukherjee","year":"2016","journal-title":"Breast Cancer Basic Clin. Res."},{"issue":"2","key":"10.1016\/j.pacs.2026.100863_b9","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1148\/radiol.2442051620","article-title":"The current status of breast MR imaging part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice","volume":"244","author":"Kuhl","year":"2007","journal-title":"Radiology"},{"key":"10.1016\/j.pacs.2026.100863_b10","doi-asserted-by":"crossref","first-page":"305","DOI":"10.2475\/ajs.s3-20.118.305","article-title":"On the production and reproduction of sound by light","volume":"s3-20","author":"Bell","year":"1880","journal-title":"Am. J. Sci."},{"key":"10.1016\/j.pacs.2026.100863_b11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2528\/PIER14032303","article-title":"Photoacoustic tomography: Principles and advances","volume":"147","author":"Xia","year":"2014","journal-title":"Electromagn. Waves"},{"key":"10.1016\/j.pacs.2026.100863_b12","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1038\/nphoton.2009.157","article-title":"Multiscale photoacoustic microscopy and computed tomography","volume":"3","author":"Wang","year":"2009","journal-title":"Nat. Photon."},{"key":"10.1016\/j.pacs.2026.100863_b13","doi-asserted-by":"crossref","first-page":"1458","DOI":"10.1126\/science.1216210","article-title":"Photoacoustic tomography: In vivo imaging from organelles to organs","volume":"335","author":"Wang","year":"2012","journal-title":"Science"},{"issue":"3","key":"10.1016\/j.pacs.2026.100863_b14","doi-asserted-by":"crossref","first-page":"767","DOI":"10.3390\/app10030767","article-title":"Photoacoustic imaging for management of breast cancer: A literature review and future perspectives","volume":"10","author":"Rao","year":"2020","journal-title":"Appl. Sci."},{"issue":"12","key":"10.1016\/j.pacs.2026.100863_b15","doi-asserted-by":"crossref","DOI":"10.1117\/1.JBO.24.12.121910","article-title":"Multidomain computational modeling of photoacoustic imaging: Verification, validation, and image quality prediction","volume":"24","author":"Akhlaghi","year":"2019","journal-title":"J. Biomed. Opt."},{"issue":"5","key":"10.1016\/j.pacs.2026.100863_b16","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.cell.2011.02.013","article-title":"Hallmarks of cancer: The next generation","volume":"144","author":"Hanahan","year":"2011","journal-title":"Cell"},{"issue":"4","key":"10.1016\/j.pacs.2026.100863_b17","doi-asserted-by":"crossref","DOI":"10.1117\/1.JBO.26.4.040901","article-title":"Deep learning in photoacoustic imaging: A review","volume":"26","author":"Deng","year":"2021","journal-title":"J. Biomed. Opt."},{"key":"10.1016\/j.pacs.2026.100863_b18","article-title":"Deep learning enhanced volumetric photoacoustic imaging of vasculature in human","volume":"10","author":"Zheng","year":"2023","journal-title":"Adv. Sci."},{"key":"10.1016\/j.pacs.2026.100863_b19","doi-asserted-by":"crossref","DOI":"10.1016\/j.pacs.2020.100197","article-title":"Y-Net: Hybrid deep learning image reconstruction for photoacoustic tomography in vivo","volume":"20","author":"Lan","year":"2020","journal-title":"Photoacoustics"},{"issue":"20","key":"10.1016\/j.pacs.2026.100863_b20","doi-asserted-by":"crossref","first-page":"7725","DOI":"10.3390\/s22207725","article-title":"Deep-E enhanced photoacoustic tomography using three-dimensional reconstruction for high-quality vascular imaging","volume":"22","author":"Zheng","year":"2022","journal-title":"Sensors"},{"issue":"11","key":"10.1016\/j.pacs.2026.100863_b21","doi-asserted-by":"crossref","first-page":"3379","DOI":"10.1109\/TMI.2020.2993835","article-title":"Deep-learning image reconstruction for real-time photoacoustic system","volume":"39","author":"Kim","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"12","key":"10.1016\/j.pacs.2026.100863_b22","doi-asserted-by":"crossref","DOI":"10.1117\/1.JBO.23.12.121622","article-title":"MCmatlab: An open-source, user-friendly, MATLAB-integrated three-dimensional Monte Carlo light transport solver with heat diffusion and tissue damage","volume":"23","author":"Marti","year":"2018","journal-title":"J. Biomed. Opt."},{"issue":"2","key":"10.1016\/j.pacs.2026.100863_b23","doi-asserted-by":"crossref","DOI":"10.1117\/1.3360308","article-title":"K-wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields","volume":"15","author":"Treeby","year":"2010","journal-title":"J. Biomed. Opt."},{"issue":"8","key":"10.1016\/j.pacs.2026.100863_b24","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/acc30b","article-title":"Towards a biomechanical breast model to simulate and investigate breast compression and its effects in mammography and tomosynthesis","volume":"68","author":"Hertel","year":"2023","journal-title":"Phys. Med. Biol."},{"issue":"7","key":"10.1016\/j.pacs.2026.100863_b25","doi-asserted-by":"crossref","DOI":"10.1002\/mp.17980","article-title":"Optimization and validation of a mechanical compression model for digital breast phantoms in mammography and tomosynthesis simulations","volume":"52","author":"Pacheco","year":"2025","journal-title":"Med. Phys."},{"issue":"19","key":"10.1016\/j.pacs.2026.100863_b26","doi-asserted-by":"crossref","first-page":"7353","DOI":"10.3390\/s22197353","article-title":"Impact of skin on microwave tomography in the lossy coupling medium","volume":"22","author":"Meaney","year":"2022","journal-title":"Sensors"},{"issue":"7","key":"10.1016\/j.pacs.2026.100863_b27","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/acbefd","article-title":"Impact of fibroglandular tissue distribution and breast shape in voxelized breast models for dosimetry in mammography","volume":"68","author":"Ferrauche","year":"2023","journal-title":"Phys. Med. Biol."},{"issue":"2","key":"10.1016\/j.pacs.2026.100863_b28","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1002\/mp.16842","article-title":"Joint AAPM task group 282\/EFOMP working group report: Breast dosimetry for standard and contrast-enhanced mammography and breast tomosynthesis","volume":"51","author":"Sechopoulos","year":"2024","journal-title":"Med. Phys."},{"key":"10.1016\/j.pacs.2026.100863_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.pacs.2025.100745","article-title":"Artifacts in photoacoustic imaging: Origins and mitigations","volume":"45","author":"Rietberg","year":"2025","journal-title":"Photoacoustics"},{"key":"10.1016\/j.pacs.2026.100863_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.pacs.2025.100735","article-title":"Signal-domain speed-of-sound correction for ring-array-based photoacoustic tomography","volume":"44","author":"Jiang","year":"2025","journal-title":"Photoacoustics"},{"key":"10.1016\/j.pacs.2026.100863_b31","doi-asserted-by":"crossref","DOI":"10.1016\/j.pacs.2025.100748","article-title":"Reconstructing multiple initial pressure and speed of sound distributions simultaneously in photoacoustic tomography","volume":"45","author":"Suhonen","year":"2025","journal-title":"Photoacoustics"},{"key":"10.1016\/j.pacs.2026.100863_b32","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1364\/BOE.555490","article-title":"Quantitative photoacoustic imaging algorithm using sparse decomposition for photoacoustic and ultrasound dual-mode imaging","volume":"16","author":"Liu","year":"2025","journal-title":"Biomed. Opt. Express"},{"key":"10.1016\/j.pacs.2026.100863_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.pacs.2025.100685","article-title":"Limited-view photoacoustic imaging reconstruction via high-quality self-supervised neural representation","volume":"42","author":"Xiao","year":"2025","journal-title":"Photoacoustics"},{"key":"10.1016\/j.pacs.2026.100863_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.pacs.2025.100749","article-title":"Wavelet-enhanced residual optimal transport for mamba-based image restoration in photoacoustic tomography","volume":"45","author":"Chan","year":"2025","journal-title":"Photoacoustics"},{"issue":"11","key":"10.1016\/j.pacs.2026.100863_b35","doi-asserted-by":"crossref","DOI":"10.1117\/1.JBO.25.11.112903","article-title":"Deep learning in photoacoustic tomography: Current approaches and future directions","volume":"25","author":"Hauptmann","year":"2020","journal-title":"J. Biomed. Opt."},{"issue":"1","key":"10.1016\/j.pacs.2026.100863_b36","first-page":"265","article-title":"Microvascular architecture in a mammary carcinoma: Branching patterns and vessel dimensions","volume":"51","author":"Less","year":"1991","journal-title":"Cancer Res."},{"issue":"22","key":"10.1016\/j.pacs.2026.100863_b37","doi-asserted-by":"crossref","first-page":"20178","DOI":"10.1364\/OE.17.020178","article-title":"Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units","volume":"17","author":"Fang","year":"2009","journal-title":"Opt. Express"},{"issue":"11","key":"10.1016\/j.pacs.2026.100863_b38","doi-asserted-by":"crossref","first-page":"R37","DOI":"10.1088\/0031-9155\/58\/11\/R37","article-title":"Optical properties of biological tissues: A review","volume":"58","author":"Jacques","year":"2013","journal-title":"Phys. Med. Biol."},{"issue":"4","key":"10.1016\/j.pacs.2026.100863_b39","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1088\/0031-9155\/38\/4\/002","article-title":"Measurement of the optical properties of the skull in the wavelength range 650-950 nm","volume":"38","author":"Firbank","year":"1993","journal-title":"Phys. Med. Biol."},{"issue":"2","key":"10.1016\/j.pacs.2026.100863_b40","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1121\/1.1336896","article-title":"Empirical relationships between acoustic parameters in human soft tissues","volume":"1","author":"Mast","year":"2000","journal-title":"Acoust. Res. Lett. Online"},{"issue":"9","key":"10.1016\/j.pacs.2026.100863_b41","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1016\/0301-5629(95)00049-6","article-title":"Ultrasonic propagation properties of excised human skin","volume":"21","author":"Moran","year":"1995","journal-title":"Ultrasound Med. Biol."},{"key":"10.1016\/j.pacs.2026.100863_b42","series-title":"3 MHz - 512 Element Curved Array, Piezocomposite Technology, Technical Datasheet cdc15131-7","year":"2023"},{"key":"10.1016\/j.pacs.2026.100863_b43","doi-asserted-by":"crossref","unstructured":"O. Ronneberger, P. Fischer, T. Brox, U-Net: Convolutional networks for biomedical image segmentation, in: Proc. Int. Conf. Med. Image Comput. Comput.-Assist. Intervent., MICCAI, 2015, pp. 234\u2013241.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10.1016\/j.pacs.2026.100863_b44","unstructured":"P. Micikevicius, et al., Mixed Precision Training, in: International Conference on Learning Representations, ICLR, 2018."},{"issue":"41","key":"10.1016\/j.pacs.2026.100863_b45","doi-asserted-by":"crossref","first-page":"eadz2046","DOI":"10.1126\/sciadv.adz2046","article-title":"High-speed photoacoustic and ultrasonic computed tomography of the breast tumor for early diagnosis with enhanced accuracy","volume":"11","author":"Huang","year":"2025","journal-title":"Sci. Adv."},{"key":"10.1016\/j.pacs.2026.100863_b46","series-title":"Attention U-Net: Learning where to look for the pancreas","author":"Oktay","year":"2018"},{"key":"10.1016\/j.pacs.2026.100863_b47","doi-asserted-by":"crossref","unstructured":"Z. Zhou, et al., UNet++: A Nested U-Net Architecture for Medical Image Segmentation, in: Proc. DLMIA\/ML-CDS, 2018, pp. 3\u201311.","DOI":"10.1007\/978-3-030-00889-5_1"},{"issue":"8","key":"10.1016\/j.pacs.2026.100863_b48","article-title":"Modeling toolchain for realistic simulation of photoacoustic data acquisition","volume":"27","author":"Muller","year":"2022","journal-title":"J. Biomed. Opt."}],"container-title":["Photoacoustics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2213597926000698?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2213597926000698?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T08:27:25Z","timestamp":1793176045000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2213597926000698"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":48,"alternative-id":["S2213597926000698"],"URL":"https:\/\/doi.org\/10.1016\/j.pacs.2026.100863","relation":{},"ISSN":["2213-5979"],"issn-type":[{"value":"2213-5979","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Real-time deep learning-based vascular recognition in clinical breast photoacoustic imaging","name":"articletitle","label":"Article Title"},{"value":"Photoacoustics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.pacs.2026.100863","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier GmbH.","name":"copyright","label":"Copyright"}],"article-number":"100863"}}