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Correlative imaging of biological tissues with apertureless scanning near-field optical microscopy and confocal laser scanning microscopy.
Stanciu, Stefan G; Tranca, Denis E; Hristu, Radu; Stanciu, George A.
Afiliação
  • Stanciu SG; Center for Microscopy-Microanalysis and Information Processing, University Politehnica of Bucharest, Bucharest, 060042, Romania.
  • Tranca DE; Center for Microscopy-Microanalysis and Information Processing, University Politehnica of Bucharest, Bucharest, 060042, Romania.
  • Hristu R; Center for Microscopy-Microanalysis and Information Processing, University Politehnica of Bucharest, Bucharest, 060042, Romania.
  • Stanciu GA; Center for Microscopy-Microanalysis and Information Processing, University Politehnica of Bucharest, Bucharest, 060042, Romania.
Biomed Opt Express ; 8(12): 5374-5383, 2017 Dec 01.
Article em En | MEDLINE | ID: mdl-29296474
ABSTRACT
Apertureless scanning near-field optical microscopy (ASNOM) has attracted considerable interest over the past years as a result of its valuable contrast mechanisms and capabilities for optical resolutions in the nanoscale range. However, at this moment the intersections between ASNOM and the realm of bioimaging are scarce, mainly due to data interpretation difficulties linked to the limited body of work performed so far in this field and hence the reduced volume of supporting information. We propose an imaging approach that holds significant potential for alleviating this issue, consisting of correlative imaging of biological specimens using a multimodal system that incorporates ASNOM and confocal laser scanning microscopy (CLSM), which allows placing near-field data into a well understood context of anatomical relevance. We demonstrate this approach on zebrafish retinal tissue. The proposed method holds important implications for the in-depth understanding of biological items through the prism of ASNOM and CLSM data complementarity.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article