{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,11]],"date-time":"2026-11-11T23:07:23Z","timestamp":1794438443535,"version":"4.9.1"},"reference-count":42,"publisher":"IOP Publishing","issue":"19","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2023YFC3402800"],"award-info":[{"award-number":["2023YFC3402800"]}]},{"name":"National Natural Science Foundation of China","award":["62027901"],"award-info":[{"award-number":["62027901"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Beijing Natural Science Foundation","award":["L232097"],"award-info":[{"award-number":["L232097"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2026,10,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    Magnetic particle imaging (MPI) is an emerging medical imaging technique for high-sensitivity and quantitative visualization of tracer distributions. Narrowband MPI achieves high signal-to-noise ratio (SNR) by selectively detecting a few harmonics. However, in its conventional implementations,the point spread function (PSF) inevitably exhibits negative lobes, which introduce anisotropic resolution and destructive signal superposition.\n                    <jats:italic>Approach.<\/jats:italic>\n                    To address this, we propose a narrowband isotropic MPI system, utilizing the field-free-line (FFL)-parallel excitation (FPE) scanning strategy to eliminate negative lobes. FPE-MPI employs single-channel acquisition with coaxial excitation and receive, applies an excitation field parallel to the FFL while maintaining a constant collinear offset field, and encodes harmonic responses on the projection plane orthogonal to the FFL.\n                    <jats:italic>Main results.<\/jats:italic>\n                    Through simulations and phantom experiments on our in-house scanner, we demonstrate that FPE-MPI eliminates the adverse effects of negative lobes, achieves isotropic imaging, and improves image quality. Compared with conventional narrowband MPI with FFL-orthogonal excitation, FPE-MPI preserves higher SNR in the acquired signals and yields robust reconstructions at low tracer concentrations, with only a modest trade-off in spatial resolution.\n                    <jats:italic>Significance.<\/jats:italic>\n                    FPE-MPI facilitates robust imaging at low tracer doses and provides a feasible scanning strategy for the development of future large field-of-view (FOV) narrowband MPI systems.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/aea399","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T22:56:47Z","timestamp":1788821807000},"page":"195027","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Narrowband isotropic magnetic particle imaging with FFL-parallel excitation"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7728-5145","authenticated-orcid":true,"given":"Zhongwei","family":"Bian","sequence":"first","affiliation":[{"name":"Beihang University"},{"name":"Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8238-4711","authenticated-orcid":true,"given":"Ziwei","family":"Chen","sequence":"additional","affiliation":[{"name":"Beihang University"},{"name":"Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2756-1628","authenticated-orcid":false,"given":"Jie","family":"He","sequence":"additional","affiliation":[{"name":"Beihang University"},{"name":"Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6732-4232","authenticated-orcid":true,"given":"Hui","family":"Hui","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences"},{"name":"University of Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4630-5223","authenticated-orcid":true,"given":"Guang","family":"Jia","sequence":"additional","affiliation":[{"name":"Xidian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3113-7259","authenticated-orcid":false,"given":"Yu","family":"An","sequence":"additional","affiliation":[{"name":"Beihang University"},{"name":"Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0498-0432","authenticated-orcid":false,"given":"Jie","family":"Tian","sequence":"additional","affiliation":[{"name":"Beihang University"},{"name":"Beihang University"},{"name":"Institute of Automation, Chinese Academy of Sciences"},{"name":"University of Chinese Academy of Sciences"},{"name":"National Key Laboratory of Kidney Diseases"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,10,8]]},"reference":[{"key":"pmbaea399bib1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TMAG.2023.3285847","type":"journal-article","article-title":"High-resolution enlarged open-bore narrowband magnetic particle imaging based on double-layer linear scanning structure","volume":"59","author":"Bai","year":"2023","journal-title":"IEEE Trans. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-02-11","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-09-07","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-08","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}