{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T23:27:42Z","timestamp":1771457262259,"version":"3.50.1"},"reference-count":68,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T00:00:00Z","timestamp":1727308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Optical microscopy is widely regarded to be an indispensable tool in healthcare and manufacturing quality control processes, although its inability to resolve structures separated by a lateral distance under ~200 nm has culminated in the emergence of a new field named fluorescence nanoscopy, while this too is prone to several caveats (namely phototoxicity, interference caused by exogenous probes and cost). In this regard, we present a triplet string of concatenated O-Net (\u2018bead\u2019) architectures (termed \u2018\u0398-Net\u2019 in the present study) as a cost-efficient and non-invasive approach to enhancing the resolution of non-fluorescent phase-modulated optical microscopical images in silico. The quality of the afore-mentioned enhanced resolution (ER) images was compared with that obtained via other popular frameworks (such as ANNA-PALM, BSRGAN and 3D RCAN), with the \u0398-Net-generated ER images depicting an increased level of detail (unlike previous DNNs). In addition, the use of cross-domain (transfer) learning to enhance the capabilities of models trained on differential interference contrast (DIC) datasets [where phasic variations are not as prominently manifested as amplitude\/intensity differences in the individual pixels unlike phase-contrast microscopy (PCM)] has resulted in the \u0398-Net-generated images closely approximating that of the expected (ground truth) images for both the DIC and PCM datasets. This thus demonstrates the viability of our current \u0398-Net architecture in attaining highly resolved images under poor signal-to-noise ratios while eliminating the need for a priori PSF and OTF information, thereby potentially impacting several engineering fronts (particularly biomedical imaging and sensing, precision engineering and optical metrology).<\/jats:p>","DOI":"10.3390\/s24196248","type":"journal-article","created":{"date-parts":[[2024,9,27]],"date-time":"2024-09-27T03:44:13Z","timestamp":1727408653000},"page":"6248","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["\u0398-Net: A Deep Neural Network Architecture for the Resolution Enhancement of Phase-Modulated Optical Micrographs In Silico"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0317-8272","authenticated-orcid":false,"given":"Shiraz S.","family":"Kaderuppan","sequence":"first","affiliation":[{"name":"Faculty of Science, Agriculture & Engineering (SAgE), Newcastle University, Newcastle upon Tyne NE1 7RU, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0810-4432","authenticated-orcid":false,"given":"Anurag","family":"Sharma","sequence":"additional","affiliation":[{"name":"Faculty of Science, Agriculture & Engineering (SAgE), Newcastle University, Newcastle upon Tyne NE1 7RU, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2697-4079","authenticated-orcid":false,"given":"Muhammad Ramadan","family":"Saifuddin","sequence":"additional","affiliation":[{"name":"Faculty of Science, Agriculture & Engineering (SAgE), Newcastle University, Newcastle upon Tyne NE1 7RU, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1146-8285","authenticated-orcid":false,"given":"Wai Leong Eugene","family":"Wong","sequence":"additional","affiliation":[{"name":"Engineering Cluster, Singapore Institute of Technology, 10 Dover Drive, Singapore 138683, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8698-7605","authenticated-orcid":false,"given":"Wai Lok","family":"Woo","sequence":"additional","affiliation":[{"name":"Computer and Information Sciences, Sutherland Building, Northumbria University, Northumberland Road, Newcastle upon Tyne NE1 8ST, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chai, J., Hao, Z., Li, A., and Ngai, E.W.T. 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