{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T03:55:15Z","timestamp":1790826915544,"version":"4.1.0"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"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":["Digital Signal Processing"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.dsp.2026.106399","type":"journal-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T15:41:09Z","timestamp":1784130069000},"page":"106399","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["CPSNet: Physics-inspired label-free deep unfolding for lung ultrasound B-Line detection"],"prefix":"10.1016","volume":"184","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6520-7537","authenticated-orcid":false,"given":"Tianqi","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oktay","family":"Karaku\u015f","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nantheera","family":"Anantrasirichai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Allinovi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alin","family":"Achim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.dsp.2026.106399_bib0001","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/TUFFC.2022.3221682","article-title":"Current advances in computational lung ultrasound imaging: a review","volume":"70","author":"Yang","year":"2022","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"issue":"1","key":"10.1016\/j.dsp.2026.106399_bib0002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/2110-5820-4-1","article-title":"Lung ultrasound in the critically ill","volume":"4","author":"Lichtenstein","year":"2014","journal-title":"Ann. Intensive Care"},{"issue":"2","key":"10.1016\/j.dsp.2026.106399_bib0003","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1002\/jum.16088","article-title":"New international guidelines and consensus on the use of lung ultrasound","volume":"42","author":"Demi","year":"2023","journal-title":"J. Ultrasound Med."},{"issue":"12","key":"10.1016\/j.dsp.2026.106399_bib0004","doi-asserted-by":"crossref","first-page":"2398","DOI":"10.1016\/j.ultrasmedbio.2022.07.007","article-title":"State of the art in lung ultrasound, shifting from qualitative to quantitative analyses","volume":"48","author":"Mento","year":"2022","journal-title":"Ultrasound Med. Biol."},{"issue":"6","key":"10.1016\/j.dsp.2026.106399_bib0005","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1378\/chest.08-1811","article-title":"Ultrasound assessment for extravascular lung water in patients undergoing hemodialysis: time course for resolution","volume":"135","author":"Noble","year":"2009","journal-title":"Chest"},{"issue":"3","key":"10.1016\/j.dsp.2026.106399_bib0006","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1093\/ndt\/gfw037","article-title":"Lung ultrasound: a novel technique for detecting fluid overload in children on dialysis","volume":"32","author":"Allinovi","year":"2017","journal-title":"Nephrol. Dial. Transplant."},{"issue":"4","key":"10.1016\/j.dsp.2026.106399_bib0007","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1007\/s00467-020-04735-9","article-title":"Lung ultrasound methods for assessing fluid volume change and monitoring dry weight in pediatric hemodialysis patients","volume":"36","author":"Fu","year":"2021","journal-title":"Pediatr. Nephrol."},{"issue":"12","key":"10.1016\/j.dsp.2026.106399_bib0008","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.7863\/ultra.32.12.2185","article-title":"Automated B-line scoring on thoracic sonography","volume":"32","author":"Brattain","year":"2013","journal-title":"J. Ultrasound Med."},{"issue":"2","key":"10.1016\/j.dsp.2026.106399_bib0009","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1109\/TUFFC.2018.2885955","article-title":"Automatic detection of B-Lines in InVivo lung ultrasound","volume":"66","author":"Moshavegh","year":"2019","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"key":"10.1016\/j.dsp.2026.106399_bib0010","series-title":"2016 IEEE International Ultrasonics Symposium (IUS)","first-page":"1","article-title":"Automatic B-line detection in paediatric lung ultrasound","author":"Anantrasirichai","year":"2016"},{"issue":"10","key":"10.1016\/j.dsp.2026.106399_bib0011","doi-asserted-by":"crossref","first-page":"2045","DOI":"10.1109\/TMI.2017.2715880","article-title":"Line detection as an inverse problem: application to lung ultrasound imaging","volume":"36","author":"Anantrasirichai","year":"2017","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"1","key":"10.1016\/j.dsp.2026.106399_bib0012","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","article-title":"Distributed optimization and statistical learning via the alternating direction method of multipliers","volume":"3","author":"Boyd","year":"2011","journal-title":"Found. Trends\/textregistered Mach. Learn."},{"key":"10.1016\/j.dsp.2026.106399_bib0013","doi-asserted-by":"crossref","unstructured":"M. Farahi, J. Aranda, H. Habibian, A. Casals, Automatic feature detection in lung ultrasound images using wavelet and radon transforms, (2023). arXiv: 2306.12780.","DOI":"10.2139\/ssrn.4670289"},{"issue":"11","key":"10.1016\/j.dsp.2026.106399_bib0014","doi-asserted-by":"crossref","first-page":"2218","DOI":"10.1109\/TUFFC.2020.3016092","article-title":"Detection of line artifacts in lung ultrasound images of COVID-19 patients via nonconvex regularization","volume":"67","author":"Karaku\u015f","year":"2020","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Contr."},{"issue":"4","key":"10.1016\/j.dsp.2026.106399_bib0015","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1109\/JBHI.2019.2936151","article-title":"Localizing B-lines in lung ultrasonography by weakly supervised deep learning, in-vivo results","volume":"24","author":"Van Sloun","year":"2019","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"8","key":"10.1016\/j.dsp.2026.106399_bib0016","doi-asserted-by":"crossref","first-page":"2676","DOI":"10.1109\/TMI.2020.2994459","article-title":"Deep learning for classification and localization of COVID-19 markers in point-of-care lung ultrasound","volume":"39","author":"Roy","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"3","key":"10.1016\/j.dsp.2026.106399_bib0017","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1109\/TMI.2021.3117246","article-title":"Integrating domain knowledge into deep networks for lung ultrasound with applications to COVID-19","volume":"41","author":"Frank","year":"2021","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.dsp.2026.106399_bib0018","series-title":"Simplifying Medical Ultrasound: Second International Workshop, ASMUS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings 2","first-page":"45","article-title":"Lung ultrasound segmentation and adaptation between COVID-19 and community-acquired pneumonia","author":"Mason","year":"2021"},{"issue":"11","key":"10.1016\/j.dsp.2026.106399_bib0019","doi-asserted-by":"crossref","first-page":"2312","DOI":"10.1109\/TUFFC.2020.3002249","article-title":"Automated lung ultrasound B-line assessment using a deep learning algorithm","volume":"67","author":"Baloescu","year":"2020","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"issue":"24","key":"10.1016\/j.dsp.2026.106399_bib0020","doi-asserted-by":"crossref","DOI":"10.3390\/app112411697","article-title":"B-line detection and localization in lung ultrasound videos using spatiotemporal attention","volume":"11","author":"Kerdegari","year":"2021","journal-title":"Appl. Sci."},{"key":"10.1016\/j.dsp.2026.106399_bib0021","series-title":"2022 IEEE International Ultrasonics Symposium (IUS)","first-page":"1","article-title":"COVID-19 feature detection with deep neural networks trained on simulated lung ultrasound B-mode images","author":"Zhao","year":"2022"},{"key":"10.1016\/j.dsp.2026.106399_bib0022","series-title":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","first-page":"1","article-title":"A semi-supervised learning approach for B-Line detection in lung ultrasound images","author":"Yang","year":"2023"},{"key":"10.1016\/j.dsp.2026.106399_bib0023","series-title":"Proceedings of the 27th International Conference on International Conference on Machine Learning","article-title":"Learning fast approximations of sparse coding","author":"Gregor","year":"2010"},{"issue":"3","key":"10.1016\/j.dsp.2026.106399_bib0024","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1109\/TPAMI.2018.2883941","article-title":"ADMM-CSNEt: a deep learning approach for image compressive sensing","volume":"42","author":"Yang","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"10.1016\/j.dsp.2026.106399_bib0025","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1109\/JSTSP.2022.3170227","article-title":"High-throughput deep unfolding network for compressive sensing MRI","volume":"16","author":"Zhang","year":"2022","journal-title":"IEEE J. Sel. Top. Signal Process."},{"issue":"2","key":"10.1016\/j.dsp.2026.106399_bib0026","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6420\/ad1a3c","article-title":"Deep unfolding as iterative regularization for imaging inverse problems","volume":"40","author":"Cui","year":"2024","journal-title":"Inverse Probl."},{"issue":"6","key":"10.1016\/j.dsp.2026.106399_bib0027","doi-asserted-by":"crossref","first-page":"1322","DOI":"10.1109\/TMI.2018.2799231","article-title":"Learned Primal-Dual reconstruction","volume":"37","author":"Adler","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"6","key":"10.1016\/j.dsp.2026.106399_bib0028","doi-asserted-by":"crossref","first-page":"1358","DOI":"10.1109\/TMI.2018.2823756","article-title":"Deep convolutional framelet denosing for low-dose CT via wavelet residual network","volume":"37","author":"Kang","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.dsp.2026.106399_bib0029","article-title":"InDuDoNet+: a deep unfolding dual domain network for metal artifact reduction in CT images","volume":"85","author":"Wang","year":"2021","journal-title":"Med. Image Anal."},{"issue":"1","key":"10.1016\/j.dsp.2026.106399_bib0030","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1109\/JPROC.2019.2932116","article-title":"Deep learning in ultrasound imaging","volume":"108","author":"Van Sloun","year":"2019","journal-title":"Proc. IEEE"},{"key":"10.1016\/j.dsp.2026.106399_bib0031","first-page":"1","article-title":"A wavelet-domain consistency-constrained compressive sensing framework based on memory-boosted guidance filtering","volume":"73","author":"Wang","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.dsp.2026.106399_bib0032","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"25149","article-title":"Ufc-Net: unrolling fixed-point continuous network for deep compressive sensing","author":"Wang","year":"2024"},{"key":"10.1016\/j.dsp.2026.106399_bib0033","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"25086","article-title":"Cpp-Net: embracing multi-scale feature fusion into deep unfolding cp-ppa network for compressive sensing","author":"Guo","year":"2024"},{"key":"10.1016\/j.dsp.2026.106399_bib0034","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.1109\/TIP.2024.3371351","article-title":"Nestd-Net: deep nesta-inspired unfolding network with dual-path deblocking structure for image compressive sensing","volume":"33","author":"Gan","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.dsp.2026.106399_bib0035","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1109\/TIP.2025.3533198","article-title":"USB-Net: Unfolding split bregman method with multi-phase feature integration for compressive imaging","volume":"34","author":"Guo","year":"2025","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.dsp.2026.106399_bib0036","series-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","first-page":"12799","article-title":"Hunet: homotopy unfolding network for image compressive sensing","author":"Shen","year":"2025"},{"issue":"5","key":"10.1016\/j.dsp.2026.106399_bib0037","doi-asserted-by":"crossref","first-page":"3992","DOI":"10.1109\/TPAMI.2025.3538896","article-title":"Invertible diffusion models for compressed sensing","volume":"47","author":"Chen","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.dsp.2026.106399_bib0038","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/TCI.2024.3420942","article-title":"RIRO: from retinex-inspired reconstruction optimization model to deep low-light image enhancement unfolding network","volume":"10","author":"Zhao","year":"2024","journal-title":"IEEE Trans. Comput. Imaging"},{"key":"10.1016\/j.dsp.2026.106399_bib0039","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"4809","article-title":"RPCANet: deep unfolding RPCA based infrared small target detection","author":"Wu","year":"2024"},{"key":"10.1016\/j.dsp.2026.106399_bib0040","series-title":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","first-page":"5573","article-title":"Multi-modality MRI semantic segmentation via edge-aware robust principal component analysis","author":"Zhao","year":"2025"},{"key":"10.1016\/j.dsp.2026.106399_bib0041","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"14781","article-title":"Neighbor2neighbor: self-supervised denoising from single noisy images","author":"Huang","year":"2021"},{"key":"10.1016\/j.dsp.2026.106399_bib0042","unstructured":"J. Lehtinen, Noise2Noise: learning image restoration without clean data, (2018). arXiv: 1803.04189."},{"key":"10.1016\/j.dsp.2026.106399_bib0043","unstructured":"M. Zhussip, S. Soltanayev, S.Y. Chun, Extending Stein\u2019s unbiased risk estimator to train deep denoisers with correlated pairs of noisy images, in: Proceedings of Advances in Neural Information Processing Systems, 2019, pp. 1465\u20131475."},{"key":"10.1016\/j.dsp.2026.106399_bib0044","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"7464","article-title":"YOLOV7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"Wang","year":"2023"},{"key":"10.1016\/j.dsp.2026.106399_bib0045","unstructured":"G. Jocher, J. Qiu, Ultralytics YOLO11, 2024, https:\/\/github.com\/ultralytics\/ultralytics."},{"issue":"6","key":"10.1016\/j.dsp.2026.106399_bib0046","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"10.1016\/j.dsp.2026.106399_bib0047","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.dsp.2026.106399_bib0048","doi-asserted-by":"crossref","unstructured":"T. Yang, N. Anantrasirichai, O. Karaku\u015f, M. Allinovi, H.C. Koydemir, A. Achim, DUBLINE: a deep unfolding network for B-line detection in lung ultrasound images, (2023). arXiv: 2311.06672.","DOI":"10.1109\/ISBI56570.2024.10635643"}],"container-title":["Digital Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1051200426005178?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1051200426005178?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T02:59:12Z","timestamp":1790823552000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1051200426005178"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":48,"alternative-id":["S1051200426005178"],"URL":"https:\/\/doi.org\/10.1016\/j.dsp.2026.106399","relation":{},"ISSN":["1051-2004"],"issn-type":[{"value":"1051-2004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CPSNet: Physics-inspired label-free deep unfolding for lung ultrasound B-Line detection","name":"articletitle","label":"Article Title"},{"value":"Digital Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.dsp.2026.106399","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"106399"}}