{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T14:19:16Z","timestamp":1788272356785,"version":"build-2803163510"},"reference-count":41,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T00:00:00Z","timestamp":1784592000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T00:00:00Z","timestamp":1784592000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82227802"],"award-info":[{"award-number":["82227802"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Magnetic particle imaging (MPI) is an emerging functional imaging modality that enables high\u2010resolution (HR) visualization of superparamagnetic iron oxide nanoparticles (SPIONs). It offers significant advantages, including high penetration capability, absence of ionizing radiation, high contrast, and exceptional temporal resolution and sensitivity, making it highly promising for a broad spectrum of biomedical and clinical applications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Although MPI holds great promise, fundamental spatial resolution is inherently constrained by the gradient field strength and the saturation magnetization physics of the SPIONs. To address the image blurring characterized by the system's point spread function (PSF) and the dependency on high\u2010gradient fields for HR imaging, this study aims to develop a robust deep learning framework to reduce reliance on high gradient hardware. We aim to achieve high\u2010fidelity resolution enhancement computationally, recovering fine structural details from low\u2010resolution inputs, thereby bypassing the need for costly hardware upgrades.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We propose a Multiscale Frequency Attention Transformer (MFAT) model, which integrates a frequency\u2010domain discriminative feedforward network (DFFN) with a multiscale attention block (MAB) to form an end\u2010to\u2010end framework for recovering HR MPI images from low\u2010resolution reconstructions. The MFAT architecture combines multiscale feature aggregation with a novel frequency attention mechanism, allowing it to capture both global context and fine local details across multiple scales while enhancing fidelity and sharpness in the frequency domain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Extensive evaluations using both simulated and real\u2010world MPI data demonstrate that the proposed MFAT model outperforms existing state\u2010of\u2010the\u2010art deep learning methods, achieving an improvement of 7.51% in peak signal\u2010to\u2010noise ratio (PSNR) in the MNIST dataset, corresponding to a gain of 2.48\u00a0dB over the second strongest baseline. Furthermore, in terms of spatial resolution, MFAT significantly reduced the full width at half maximum (FWHM) by 17.86% on the complex FIVES vascular structures compared to the second\u2010performing baseline, verifying its superior capability in recovering high\u2010frequency details.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Thus, MFAT provides an effective solution for enhancing spatial resolution in MPI image reconstruction and significantly improves image quality. This advancement holds strong potential to facilitate the translation of MPI technology into more refined clinical applications.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70565","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T05:26:21Z","timestamp":1784697981000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multiscale frequency attention transformer for resolution enhancement in magnetic particle imaging"],"prefix":"10.1002","volume":"53","author":[{"given":"Wenjing","family":"Jiang","sequence":"first","affiliation":[{"name":"School of Control Science and Engineering Shandong University  Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinzhuang","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering Shandong University  Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoli","family":"Yang","sequence":"additional","affiliation":[{"name":"Weifang Xinli Superconducting Magnet Technology Co., Ltd  Weifang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"He","sequence":"additional","affiliation":[{"name":"School of Life Science and Technology Xidian University  Xi'an Shaanxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moritz","family":"Wildgruber","sequence":"additional","affiliation":[{"name":"Klinikum der Universit\u00e4t M\u00fcnchen  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Opto\u2010Electronic Engineering and Ministry of Education Key Laboratory of Precision Opto\u2010Mechatronics Technology Beihang University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianshe","family":"Zhao","sequence":"additional","affiliation":[{"name":"Children's Hospital Affiliated to Shandong University  Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaopeng","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering Shandong University  Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,21]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature03808"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.a5896"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1103\/physrevapplied.18.024077"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1186\/s42492\u2010022\u201000120\u20105"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467\u2010019\u201009704\u2010x"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.3554646"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cbpa.2018.04.014"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010017\u201006992\u20105"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.iliver.2022.10.003"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2020.2965724"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.18416\/ijmpi.2022.2203069"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41551\u2010019\u20100506\u20100"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.7150\/thno.77886"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/52\/21\/001"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2011.2113188"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/abad7c"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1039\/c7nr05502a"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1063\/5.0220219"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.18036"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/acb584"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2022.3189693"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.202306450"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/ad3c90"},{"key":"e_1_2_9_25_1","doi-asserted-by":"crossref","unstructured":"HalkolaA RahmerJ GleichB BorgertJ BuzugT.System calibration unit for magnetic particle imaging: system matrix. In:2013 International Workshop on Magnetic Particle Imaging (IWMPI).IEEE;2013:1. doi:10.1109\/iwmpi.2013.6528344","DOI":"10.1109\/IWMPI.2013.6528344"},{"key":"e_1_2_9_26_1","doi-asserted-by":"crossref","unstructured":"SohJW ParkGY JoJ ChoNI.Natural and realistic single image super\u2010resolution with explicit natural manifold discrimination. In:2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR).IEEE;2019:8114\u20108123. doi:10.1109\/cvpr.2019.00831","DOI":"10.1109\/CVPR.2019.00831"},{"key":"e_1_2_9_27_1","doi-asserted-by":"crossref","unstructured":"LiangJ CaoJ SunG ZhangK Van GoolL TimofteR SwinIR: Image Restoration Using Swin Transformer. In:IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW). Published online October 1 2021:1833\u20101844. doi:10.1109\/iccvw54120.2021.00210","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/tim.2025.3568956"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2025.3525948"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2010.2052284"},{"key":"e_1_2_9_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2011.2125982"},{"key":"e_1_2_9_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2013.2257177"},{"key":"e_1_2_9_33_1","unstructured":"ShazeerN.GLU variants improve transformer. arXiv preprint arXiv:2002.05202.2020.https:\/\/arxiv.org\/abs\/2002.05202"},{"key":"e_1_2_9_34_1","volume-title":"FFL\u2010MPI\u2010Data (v.1.0): a public projection imaging dataset for field free line magnetic particle imaging","author":"Li Y","year":"2025"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/ac6e24"},{"key":"e_1_2_9_36_1","doi-asserted-by":"crossref","unstructured":"GaoY HeN GeD ZhangZ WangY ZhuS.A method for improving the sensitivity based on adaptive compensation in MPI. In:IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA).IEEE;2024:1\u20105. doi:10.1109\/civemsa58715.2024.10586649","DOI":"10.1109\/CIVEMSA58715.2024.10586649"},{"key":"e_1_2_9_37_1","doi-asserted-by":"publisher","DOI":"10.3745\/kipstd.2011.18d.5.323"},{"key":"e_1_2_9_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/18.850703"},{"key":"e_1_2_9_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2022.108902"},{"key":"e_1_2_9_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103280"},{"key":"e_1_2_9_41_1","doi-asserted-by":"crossref","unstructured":"WangZ CunX BaoJ LiuJ Uformer: A general u\u2010shaped transformer for image restoration. In:Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR).2022:17601\u201017610.","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"e_1_2_9_42_1","first-page":"240","volume-title":"Lecture Notes in Computer Science","author":"Gao N","year":"2024"}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70565","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mp.70565","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70565","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T13:43:46Z","timestamp":1788270226000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.70565"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,21]]},"references-count":41,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["10.1002\/mp.70565"],"URL":"https:\/\/doi.org\/10.1002\/mp.70565","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,21]]},"assertion":[{"value":"2026-01-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-19","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-07-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70565"}}