Browsing by Subject "Monte Carlo simulations"

Now showing 1 - 4 of 4

Open Access
Frequency response analysis and reconstruction weighting schemes for MR elastography
(2020-09) Arıyürek, Cemre
Magnetic resonance elastography (MRE) non-invasively and quantitatively assesses the elasticity of the in-vivo tissue. In MRE, shear waves are induced to the tissue by an actuator, while phase-contrast images are obtained by magnetic resonance imaging (MRI). Finally, elasticity maps are generated using displacement information carried by phase-contrast images. The direction and frequency of the induced shear waves could be crucial in MRE. Here, it is demonstrated by the frequency response MRE simulations that modes of the shear waves can be observed in the brain during MR elastography with high shear wave displacement values at the mode frequencies. High shear wave displacements, 10-20 times of the applied displacement, were observed at mode frequencies in phantom MRE experiments. The second part of the thesis focuses on weighting schemes to combine multiple elasticity maps reconstructed from data collected for different excitation frequencies and motion direction. A new weighting scheme, which maximizes the signal-to-noise ratio (SNR) of the final wave speed map, has been proposed for tomoelastography and Helmholtz inversions. For both inversion techniques, considering the noise on the complex MRI signal, the SNR of the reconstructed wave speed map was formulated by an analytical approach assuming a high SNR. Thus, with the proposed SNR weighting method, while not altering the accuracy or spatial resolution of the wave speed map, the SNR of the wave speed map has been improved by 2 and 1.6 times for tomoelastography and Helmholtz inversion, respectively. The bias occurring for low SNR data cases was eliminated in tomoelastography and reduced in Helmholtz inversion with the proposed SNR-weighted reconstructions. Similarly, a strain-based weighting for MRE reconstruction has been introduced. Experimental results demonstrated that strain weights could prevent artifacts at the boundaries of encapsulated tumors or tissues with membranes; however, further examination is required. In this thesis, two independent contributions have been made to the field of magnetic resonance elastography. By showing the existence of modes of the shear waves in the body, new fronts are opened in the MRE actuation methods and safety. The improvements in the elasticity map inversions could lead to the routine use of MRE in clinical practice.
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
Learning based control compensation for multi-axis gimbal systems using inverse and forward dynamics
(2021-09) Leblebicioğlu, Damla
Unmanned aerospace vehicles (such as rockets, drones, and satellites) usually carry sensors as their primary payload. These sensors (i.e., electro-optical and/or infrared imaging cameras) are used for image processing, target tracking, surveillance, mapping, and providing high-resolution imagery for environmental surveys. It is crucial to obtain a steady image in all of those applications. This is typically accomplished by using multi-axis gimbal systems. This study concentrates on the modeling and control of a multi-axis gimbal system that will be mounted on a surface-to-surface tactical missile. A novel and fully detailed procedure is proposed to derive the nonlinear and highly coupled EOMs (Equations of Motion) of the two-axis gimbal system. Different from the existing works, Forward Dynamics of the two-axis gimbal system is modeled using multi-body dynamics modeling techniques. In addition to Forward Dynamics model, Inverse Dynamics model is generated to estimate the complementary torques associated with the state and mechanism-dependent, complex disturbances acting on the system. Forward and Inverse Dynamics models are used in Monte Carlo Simulations (MCSs) for Sensitivity Analysis. A multilayer perceptron (MLP) structure based disturbance compensator is implemented to cope with external and internal disturbances and parameter uncertainities through torque input channel. Comparisons with well known controllers such as cascaded PID, ADRC (Active Disturbance Rejection Control), Inverse Dynamics based controllers show that the NN (neural network)-based controller is more succesful in the full operational range without requiring any tuning or adjustment. Implementation of MLP assisted closed-loop control with simulations using Simulink® are performed. Finally, proposed control algorithms are tested on the physical system by using Simulink® Real-Time (xPC Target). Comparative results are presented in figures and tables in the thesis.
Open Access
SNR weighting for shear wave speed reconstruction in tomoelastography
(John Wiley & Sons Ltd., 2020-08-06) Arıyürek, Cemre; Taşdelen, Bilal; İder, Yusuf Ziya; Atalar, Ergin
In tomoelastography, to achieve a final wave speed map by combining reconstructions obtained from all spatial directions and excitation frequencies, the use of weights is inevitable. Here, a new weighting scheme, which maximizes the signal-to-noise ratio (SNR) of the final wave speed map, has been proposed. To maximize the SNR of the final wave speed map, the use of squares of estimated SNR values of reconstructed individual maps has been proposed. Therefore, derivations of the SNR of the reconstructed wave speed maps have become necessary. Considering the noise on the complex MRI signal, the SNR of the reconstructed wave speed map was formulated by an analytical approach assuming a high SNR, and the results were verified using Monte Carlo simulations (MCSs). It has been assumed that the noise remains approximately Gaussian when the image SNR is high enough, despite the nonlinear operations in tomoelastography inversion. Hence, the SNR threshold was determined by comparing the SNR computed by MCSs and analytical approximations. The weighting scheme was evaluated for accuracy, spatial resolution and SNR performances on simulated phantoms. MR elastography (MRE) experiments on two different phantoms were conducted. Wave speed maps were generated for simulated 3D human abdomen MRE data and experimental human abdomen MRE data. The simulation results demonstrated that the SNR-weighted inversion improved the SNR performance of the wave speed map by a factor of two compared to the performance of the original (i.e., amplitude-weighted) reconstruction. In the case of a low SNR, no bias occurred in the wave speed map when SNR weighting was used, whereas 10% bias occurred when the original weighting (i.e., amplitude weighting) was used. Thus, while not altering the accuracy or spatial resolution of the wave speed map with the proposed weighting method, the SNR of the wave speed map has been significantly improved.