Enhancing Super-Resolution Microscopy Through a Synergistic Approach with Generative Machine Learning Models

Radu Ciucu; Ioana Raluca Adochiei; Florin-Ciprian Argatu; Serban Teodor Nicolescu; Gladiola Petroiu; Felix–Constantin Adochiei

doi:10.1007/978-3-031-62520-6_36

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Enhancing Super-Resolution Microscopy Through a Synergistic Approach with Generative Machine Learning Models

Radu Ciucu Ioana Raluca Adochiei Florin-Ciprian Argatu Serban Teodor Nicolescu Gladiola Petroiu Felix–Constantin Adochiei

Year: 2024 World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany Pages: 313-323 Publisher: Springer Nature

DOI: 10.1007/978-3-031-62520-6_36

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Keywords:

Generative grammar Resolution (logic) Microscopy Computer science Artificial intelligence Physics Optics

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Cell Image Analysis Techniques

Life Sciences → Biochemistry, Genetics and Molecular Biology → Biophysics

Advanced Fluorescence Microscopy Techniques

Life Sciences → Biochemistry, Genetics and Molecular Biology → Biophysics

Digital Holography and Microscopy

Physical Sciences → Physics and Astronomy → Atomic and Molecular Physics, and Optics

Enhancing Super-Resolution Microscopy Through a Synergistic Approach with Generative Machine Learning Models

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