{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T10:08:56Z","timestamp":1787652536885,"version":"build-2736575974"},"reference-count":36,"publisher":"Optica Publishing Group","issue":"3","license":[{"start":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:00:00Z","timestamp":1770768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR-OA"},{"start":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:00:00Z","timestamp":1770768000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82260368"],"award-info":[{"award-number":["82260368"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"},{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["2022YFC3400600"],"award-info":[{"award-number":["2022YFC3400600"]}]},{"name":"Innovational Fund for Scientific and Technological Personnel of Hainan Province","award":["KJRC2023C03"],"award-info":[{"award-number":["KJRC2023C03"]}]}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Biomed. Opt. Express"],"published-print":{"date-parts":[[2026,3,1]]},"abstract":"<jats:p>\n                    Colorimetry camera-based single-molecule localization microscopy (CC-STORM) employs a simple optical setup to facilitate the simultaneous imaging of two or more targets at the nanoscale, but it suffers from a high data rejection rate. A recently reported deep learning-based algorithm (called CC-DeepSTORM) reduced the data rejection rate of two-color CC-STORM from 70% to 40%, while achieving crosstalk of 1%. However, when applying this algorithm to regions with dense emitters, it faces challenges with structural artifacts and low detection rates. Here, we propose CC-DenseSTORM, featuring an attention-gated standard-convolution U-Net to eliminate structural artifacts and a dual-channel adaptive classification network for robust dye classification. Simulations demonstrate that, even at a high density of 5 emitters\/\u00b5m\n                    <jats:sup>2<\/jats:sup>\n                    , CC-DenseSTORM improves the detection rate by 2-fold compared to CC-DeepSTORM, while maintaining the data rejection rate below 30%. In experimental imaging of multiple myeloma cells, CC-DenseSTORM achieves &lt;1% crosstalk (matching the state of the art), thus enabling simultaneous quantification of the densities of CD38 and BCMA, offering great potential for advancing dual-target immunotherapy.\n                  <\/jats:p>","DOI":"10.1364\/boe.587452","type":"journal-article","created":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T12:00:09Z","timestamp":1770292809000},"page":"1319","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["CC-DenseSTORM: deep learning enables colorimetry camera-based simultaneous two-color single-molecule localization microscopy with dense emitters"],"prefix":"10.1364","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9585-7750","authenticated-orcid":true,"given":"Yaolong","family":"Li","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03q648j11","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weibing","family":"Kuang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9366-6586","authenticated-orcid":true,"given":"Zhengxia","family":"Wang","sequence":"additional","affiliation":[{"name":"Hainan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5703-3610","authenticated-orcid":true,"given":"Yingjun","family":"Zhang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03q648j11","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2400-966X","authenticated-orcid":true,"given":"Zhen-Li","family":"Huang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03q648j11","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"key":"boe-17-3-1319-R1","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1038\/s41586-025-09518-6","type":"journal-article","volume":"647","author":"Li","year":"2025","journal-title":"Nature"},{"key":"boe-17-3-1319-R2","doi-asserted-by":"publisher","first-page":"568","DOI":"10.3324\/haematol.2022.281339","type":"journal-article","volume":"108","author":"Garc\u00eda-Guerrero","year":"2022","journal-title":"Haematologica"},{"key":"boe-17-3-1319-R3","doi-asserted-by":"publisher","first-page":"3371","DOI":"10.1038\/s41467-024-47801-8","type":"journal-article","volume":"15","author":"Shi","year":"2024","journal-title":"Nat. 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