Nonlinear Optical Microscopy Signal Processing Strategies in Cancer | Zendy

Javier Adur | Zendy; Hernandes F. Carvalho | Zendy; Carlos L. César | Zendy; Víctor H. Casco | Zendy

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Nonlinear Optical Microscopy Signal Processing Strategies in Cancer

Author(s) -

Javier Adur,

Hernandes F. Carvalho,

Carlos L. César,

Víctor H. Casco

Publication year - 2014

Publication title -

cancer informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.606

H-Index - 31

ISSN - 1176-9351

DOI - 10.4137/cin.s12419

Subject(s) - image processing , autofluorescence , microscopy , computer science , cancer imaging , digital image processing , fast fourier transform , artificial intelligence , biomedical engineering , cancer , optics , algorithm , medicine , physics , image (mathematics) , fluorescence

This work reviews the most relevant present-day processing methods used to improve the accuracy of multimodal nonlinear images in the detection of epithelial cancer and the supporting stroma. Special emphasis has been placed on methods of non linear optical (NLO) microscopy image processing such as: second harmonic to autofluorescence ageing index of dermis (SAAID), tumor-associated collagen signatures (TACS), fast Fourier transform (FFT) analysis, and gray level co-occurrence matrix (GLCM)-based methods. These strategies are presented as a set of potential valuable diagnostic tools for early cancer detection. It may be proposed that the combination of NLO microscopy and informatics based image analysis approaches described in this review (all carried out on free software) may represent a powerful tool to investigate collagen organization and remodeling of extracellular matrix in carcinogenesis processes.

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