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<p>Image registration has become an indispensable tool in medical diagnosis and intervention. The increasing need for speed and accuracy in clinical applications have motivated researchers to focus on developing fast and reliable registration algorithms. In particular, advanced deformable registration routines are emerging for medical applications involving soft-tissue organs such as brain, breast, kidney, liver, prostate, etc. Computational complexity of such algorithms are significantly higher than those of conventional rigid and affine methods, leading to substantial increases in execution time. In this thesis, we present a parallel implementation of a newly developed deformable image registration algorithm by Marami et al. [1] using the Computer Unified Device Architecture (CUDA). The focus of this study is on acceleration of the computations on a Graphics Processing Unit (GPU) to reduce the execution time to nearly real-time for diagnostic and interventional applications. The algorithm co-registers preoperative and intraoperative 3-dimensional magnetic resonance (MR) images of a deforming organ. It employs a linear elastic dynamic finite-element model of the deformation and distance measures such as mutual information and sum of squared difference to align volumetric image data sets. In this study, we report a parallel implementation of the algorithm for 3D-3D MR registration based on SSD on a CUDA capable NVIDIA GTX 480 GPU. Computationally expensive tasks such as interpolation, displacement and force calculation are significantly accelerated using the GPU. The result of the experiments carried out with a realistic breast phantom tissue shows a 37-fold speedup for the GPUbased implementation compared with an optimized CPU-based implementation in high resolution MR image registration. The CPU is a 3.20 GHz Intel core i5 650 processor with 4GB RAM that also hosts the GTX 480 GPU. This GPU has 15 streaming multiprocessors, each with 32 streaming processors, i.e. a total of 480 cores. The GPU implementation registers 3D-3D high resolution (512×512×136) image sets in just over 2 seconds, compared to 1.38 and 23.25 minutes for CPU and MATLAB-based implementations, respectively. Most GPU kernels which are employed in 3D-3D registration algorithm also can be employed to accelerate the 2D-3D registration algorithm in [1].</p> / Master of Applied Science (MASc)

<p>The typical High Dose Rate (HDR) lung brachytherapy procedure involves inserting treatment catheters into the bronchi next to the tumour location using a bronchoscope. The anterior-posterior and lateral fluoroscopy images are acquired in order to localize the catheters prior to treatment. Although, these images enable accurate reconstruction of the catheter location, they do not allow for the visualization of the tumour or organs-at-risk due to poor soft tissue contrast. Although CT images offer an improved soft tissue contrast, moving the patient with catheters in place prior to each treatment is impractical.</p> <p>An alternative option is to use prior diagnostic or external beam radiation treatment planning CT images. These images cannot be used for treatment planning directly because of the variation in patient positioning between the CT and orthogonal images acquisition. In order to account for positioning differences, a 2D/3D registration algorithm that registers the orthogonal images with a previously acquired CT data was developed. The algorithm utilizes a rigid registration model based on a pixel/voxel intensity matching approach. A similarity measure combining normalized mutual information (NMI), image gradient, and intensity difference was developed. Evaluation of the algorithm was performed using tissue equivalent phantoms, and, in the clinical setting using data from six patients. The mean registration error was 2.1 mm and 3.2 mm for phantoms and patients respectively.</p> <p>External objects such as the treatment table and ECG leads are often in CT images, affecting the above mentioned 2D/3D registration. To address this, an algorithm for automatic removal of external objects from CT images was developed. This was applied to automatic contouring and removal of the fiducial markers in CT images used for external beam radiation therapy treatment planning for breast cancer. The algorithm was further modified to compute the girth of patients as part of a diagnostic radiology clinical trial.</p> / Doctor of Philosophy (PhD)

This thesis outlines the development of an automatic image registration algorithm for matching 3D CT data to 2D fluoroscope X-ray images. The registration is required in order to calculate a transformation for measurements in the 2D image into the 3D representation. The algorithm achieves the registration by generating digitally reconstructed radiographs from the CT data set. The radiographs are 2D projection images, and therefore may be compared with the 2D Fluoroscope images. The X-ray and fluoroscope images were compared using the photometric-based registration algorithm, pseudocorrelation, with X^2 as the distance metric. An automated search algorithm was implemented using the Downhill Simplex of Nelder and Meade. The algorithm was successful in locating the position and orientation of the CT data set for calculating a digitally reconstructed radiograph to match the fluoroscope image. The CT data set was located with a maximum mean position error of 2.4 mm in xy, 4.4 mm in z, and xyz axial rotation within 0.5°. The standard deviation given 1800 random starting locations was 9.3 mm in x, 12.7 mm in y, 16.9 mm in z, xz axial rotation 2.5°, and y axial rotation of 1.9°. The search algorithm was successful in handling gross misalignment, however there were difficulties in convergence once within the vicinity of the global minimum. It is suggested to implement a hybrid search technique, switching to a conjugate gradient search algorithm once in the vicinity of the global minimum. An additional refinement would be a possible change of the distant metric, or the registration algorithm, once within the vicinity of the global minimum. Additional investigation needs to be directed towards testing the algorithm with live fluoroscope and CT data. This is required in order to assess registration performance when comparing different imaging modalities. / Thesis / Master of Engineering (ME)

Nearly 350 years of politically sanctioned domination over Blacks ended with the passage of the Voting Rights Act (VRA) in 1965. The federal regulation of voter and election law sought to end retrogressions in representation by intentional or effectual laws. In the VRA's wake, race based politics and policy rooted in White supremacy were curtailed with the gradual representation of communities of color in all levels of government. Shelby County v Holder (2013) obstructed progress by effectively terminating preclearance of legal changes by the federal government. Since Shelby, retrogression of voter registration is once again on the rise. Remedies for retrogression require litigation and matriculation through the courts. This process is time consuming and allows states to conduct election law with minimal interruption until decisions are rendered. Research predating the passage of the Voting Rights Act by Matthews and Prothro indicated that there was a significant correlation between growing minority populations and the severity of election and voter laws. This paper seeks to determine if growing minority populations, in part due to disproportionately large in-migration, correlates with declining voter registration rates. These voter registration rates are due to substantive legal changes and procedural enforcement changes. Retrogression in Black, White, and Latinx is shown in analyzing state voter registration data. Using a time-series multivariate analysis to compare impact on Black, Latinx, and White communities across counties in North Carolina and Alabama, this paper determines that growing minority populations and in-migration do not have consistent statistical significance in explaining declining voter registration rates for Blacks and Latinx communities based on data from the US Census Bureau's American Community Survey and the Alabama and North Carolina Board of Elections. Periodic retrogression in voter registration for the Black community show statistically significant positive associations with increasing population sizes. The Black community experiences retrogression via statistically significant negative associations in national election years, and Black voter registration rates recover in off-year elections. Data indicates that there may be a decrease in representation of larger minority communities that Black communities are able to overcome. There is a strong association between decreasing voter registration rates and larger Latinx communities while the opposite is true of Black communities. The Latinx community voter registration have statistically significant negative associations with increasing population sizes and during national election years, with recovering registration rates in off-year elections. / Master of Arts / Nearly 350 years of politically sanctioned domination over Blacks ended with the passage of the Voting Rights Act (VRA) in 1965. The federal regulation of voter and election law sought to end retrogressions in representation by intentional or effectual laws. In the VRA's wake, race based politics and policy rooted in White supremacy were curtailed with the gradual representation of communities of color in all levels of government. Shelby County v Holder (2013) obstructed progress by effectively terminating preclearance of legal changes by the federal government. Since Shelby, retrogression of voter registration is once again on the rise. Remedies for retrogression require litigation and matriculation through the courts. This process is time consuming and allows states to conduct election law with minimal interruption until decisions are rendered. Research predating the passage of the Voting Rights Act by Matthews and Prothro indicated that there was a significant correlation between growing minority populations and the severity of election and voter laws. This paper seeks to determine if growing minority populations, in part due to disproportionately large in-migration, correlates with declining voter registration rates. These voter registration rates are due to substantive legal changes and procedural enforcement changes. Retrogression in Black, White, and Latinx is shown in analyzing state voter registration data. Findings determine that for Black, Latinx, and White communities across counties in North Carolina and Alabama, growing minority populations and in-migration do not have significance in explaining declining voter registration rates for Blacks based on data from the US Census Bureau's American Community Survey and the Alabama and North Carolina Board of Elections. However, voter registration rates decrease as Latinx communities increase in size while the opposite is true of Black communities. Retrogression in Black and Latinx voter registration during national election years and rebound in off-year elections.