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A"],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:p>Label-free imaging has gained significant attention in the community since it provides the analysis of the tissue without tagging a specific dye. Auto-fluorescence microscopy provides information on the molecular distribution of different endogenous fluorophores present in the sample. On the other hand, quantitative phase microscopy provides information about the refractive index and morphology of the constituents of the sample. The simultaneous information about the sample from the same field of view provides complete information about the specimen. In the present work, a technique is introduced for simultaneously studying the morpho-molecular information of the sample from the same field of view using auto-fluorescence and quantitative phase microscopy. The approach is first validated on fluorescent polystyrene microspheres by extracting the phase map of the microspheres along with the autofluorescence information. The phase values and autofluorescence spectra provide validation for the proposed technique. After the successful validation of the approach, the study is extended to unlabeled human tissue sections for studying oral squamous cell carcinoma and normal tissue sections. The study proves that the simultaneous morpho-molecular information about the sample helps classify the tissue with higher accuracy and can be useful for clinical examinations.<\/jats:p>","DOI":"10.1364\/josaa.595871","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T14:00:09Z","timestamp":1779372009000},"page":"D95","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Simultaneous morpho-molecular microscopy for label-free tissue classification"],"prefix":"10.1364","volume":"43","author":[{"given":"Himanshu","family":"Joshi","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/049tgcd06","id-type":"ROR","asserted-by":"publisher"}]},{"name":"UiT The Arctic University of Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Varun","family":"Surya","sequence":"additional","affiliation":[{"name":"All India Institute of Medical Sciences (AIIMS)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5794-2157","authenticated-orcid":true,"given":"Dalip Singh","family":"Mehta","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/049tgcd06","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,6,10]]},"reference":[{"key":"josaa-43-8-D95-R1","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.1038\/s41566-023-01299-6","type":"journal-article","volume":"17","author":"Shaked","year":"2023","journal-title":"Nat. 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All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}