Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/DB135096-ED6C-4374-B144-FFE370461A5B | ||
| Έτος | 2018 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | G. Bauman, S. Shrestha, K. Mallinson, Z. Giakos, M. Surovich, Y. Wang, G. Livanos, M. Zervakis, N. Ying and G.C. Giakos, "Multiresolution bioinspired cross-polarized imaging and biostatistics of lung cancer tissue samples," in 2017 IEEE International Conference on Imaging Systems and Techniques, 2018, pp. 1-6. doi: 10.1109/IST.2017.8261458 https://doi.org/10.1109/IST.2017.8261458 | ||
| Εμφανίζεται στις Συλλογές |
The novelty of this study consists in the development of a technique for efficient discrimination of lung tissues pathologies consisting of squamous carcinomas, at varying grade, stage, including necrotic tissues. Polarimetric measurements using a home-built Whole Slide Imaging (WSI) polarized light imaging system, operating under diffuse reflectance, were obtained. Images were acquired, under diffuse reflectance imaging, then processed through wavelet decomposition, statistically analyzed and compared using Pearson correlation coefficient analysis. The outcome of this study indicates that cross-polarized polarimetric wavelet analysis of samples is proved superior with respect the polarization per se analysis, providing therefore enhanced discrimination. The novel observations of this study can be applied towards the implementation of bioinspired vision systems as well as for further enhancement of the quality of imaging systems and devices in the areas of Whole-Slide Imaging (WSI) in conjunction to virtual Microscopy (VM) and imaging of margins.
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