Browsing by Subject "Contrast Enhancement"

Now showing 1 - 3 of 3

Open Access
Influence of phase function on modeled optical response of nanoparticle-labeled epithelial tissues
(2011) Cihan, C.; Arifler, D.
Metal nanoparticles can be functionalized with biomolecules to selectively localize in precancerous tissues and can act as optical contrast enhancers for reflectance-based diagnosis of epithelial precancer. We carry out Monte Carlo (MC) simulations to analyze photon propagation through nanoparticle-labeled tissues and to reveal the importance of using a proper form of phase function for modeling purposes. We first employ modified phase functions generated with a weighting scheme that accounts for the relative scattering strengths of unlabeled tissue and nanoparticles. To present a comparative analysis, we repeat ourMCsimulations with simplified functions that only approximate the angular scattering properties of labeled tissues. The results obtained for common optical sensor geometries and biologically relevant labeling schemes indicate that the exact form of the phase function used as model input plays an important role in determining the reflectance response and approximating functions often prove inadequate in predicting the extent of contrast enhancement due to labeling. Detected reflectance intensities computed with different phase functions can differ up to ̃60% and such a significant deviation may even alter the perceived contrast profile. These results need to be taken into account when developing photon propagation models to assess the diagnostic potential of nanoparticle-enhanced optical measurements. © 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).
Open Access
Model-based spectral analysis of photon propagation through nanoparticle-labeled epithelial tissues
(SPIE, 2011) Cihan, Can; Arifler, D.
Metal nanoparticles can function as optical contrast enhancers for reflectance-based diagnosis of epithelial precancer. We carry out Monte Carlo simulations to model photon propagation through normal tissues, unlabeled precancerous tissues, and precancerous tissues labeled with gold nanospheres and we compute the spectral reflectance response of these different tissue states. The results indicate that nanoparticle-induced changes in the spectral reflectance profile of tissues depend not only on the properties of these particles but also on the source-detector geometry used. When the source and detector fibers are oriented side by side and perpendicular to the tissue surface, the reflectance intensity of precancerous tissue is lower compared to that of normal tissue over the entire wavelength range simulated and addition of nanospheres enhances this negative contrast. When the fibers are tilted toward each other, the reflectance intensity of precancerous tissue is higher compared to that of normal tissue and labeling with nanospheres causes a significant enhancement of this positive contrast. The results also suggest that model-based spectral analysis of photon propagation through nanoparticle-labeled tissues provides a useful framework to quantify the extent of achievable contrast enhancement due to external labeling and to assess the diagnostic potential of nanoparticle-enhanced optical measurements. © 2011 SPIE-OSA.
Open Access
Phase-based techniques for image and video processing applications
(2017-12) Çakır, Serdar
In this thesis, phase information is utilized to address several issues in image processing applications; namely image quality assessment, image contrast enhancement, and visual object tracking. The classical two-dimensional (2D) melcepstrum features, which ignore the phase information by design, are enhanced with image phase to form the 2D complex mel-cepstrum features. While integrating the phase information with the existing ceptral features, the unwrapping of phase information is carried out. The 2D complex mel-cepstrum features are fed into a regression scheme to map the feature matrices to subjective scores for the assessment of image quality. A Fourier domain approach for contrast enhancement of microscopy images is developed. The enhancement framework determines the frequency components in which the phase transitions are signifi- cant. The significant spectrum components are amplified by a factor depending on the level of transitions. In this way, phase variations are translated into amplitude changes which directly contribute to the enhancement process. Selective variation, which is an extension to the classical total variation framework, is introduced to determine the appropriate parameter set for the enhancement framework. The selective variation scheme evaluates the variations of the image in the high-frequency regions. A visual object tracking scheme based on image phase information is proposed. The main aim of the proposed scheme is to reduce the computational complexity of cross-correlation based matching frameworks. Starting from the derivation of normalized cross-correlation function, the tracking solution is simplified to a phase minimization problem under certain assumptions. The utilization of look-up tables for phase shifts enables a further decrease in computational cost.