Thesis (Ph. D.)--University of Iowa, 2007. / Thesis supervisor: Gary E. Christensen. Includes bibliographical references (leaves 159-173).

Thesis supervisor: Gary E. Christensen. Includes bibliographic references (p. 110-113).

No description available.

Image registration is the task of aligning two or more images into the same reference frame to compare or distinguish the images. The majority of registration methods deal with registering only two images at a time. Recently, a clustering method that concurrently registers more than two multi-sensor images was proposed, dubbed ensemble clustering. In this thesis, we apply the ensemble clustering method to deformable registration scenario for the first time. Non-rigid deformation is implemented by a FFD model based on B-splines. A regularization term is added to the cost function of the method to limit the topology and degree of the allowable deformations. However, the increased degrees of freedom in the transformations caused the Newton-type optimization process to become ill-conditioned. This made the registration process unstable. We solved this problem by using the matrix approximation afforded by the singular value decomposition (SVD). Experiments showed that the method is successfully applied to non-rigid multi-sensor ensembles and overall yields better registration results than methods that register only 2 images at a time. In addition, we parallelized the ensemble clustering method to accelerate the performance of the method. The parallelization was implemented on GPUs using CUDA (Compute Unified Device Architecture) programming model. The GPU implementation greatly reduced the running time of the method.

Image registration is the task of aligning two or more images into the same reference frame to compare or distinguish the images. The majority of registration methods deal with registering only two images at a time. Recently, a clustering method that concurrently registers more than two multi-sensor images was proposed, dubbed ensemble clustering. In this thesis, we apply the ensemble clustering method to deformable registration scenario for the first time. Non-rigid deformation is implemented by a FFD model based on B-splines. A regularization term is added to the cost function of the method to limit the topology and degree of the allowable deformations. However, the increased degrees of freedom in the transformations caused the Newton-type optimization process to become ill-conditioned. This made the registration process unstable. We solved this problem by using the matrix approximation afforded by the singular value decomposition (SVD). Experiments showed that the method is successfully applied to non-rigid multi-sensor ensembles and overall yields better registration results than methods that register only 2 images at a time. In addition, we parallelized the ensemble clustering method to accelerate the performance of the method. The parallelization was implemented on GPUs using CUDA (Compute Unified Device Architecture) programming model. The GPU implementation greatly reduced the running time of the method.

The aim of the research was: *to gain a better understanding on the concepts of Human-computer interaction (HCI) in general and the application of HCI principles in this field; to gain a better understanding of electronic registration systems (e-registration systems) and the use of web forms for this purpose; to gain a better understanding of which HCI principles could be applied to the design of a web form for e-registration; to apply the identified HCI principles to an example of a web form that was to be created; •to evaluate the design of the web form by means of different data-gathering techniques, and •to redesign the web form according to the data obtained from method triangulation. In order to achieve these objectives, the research used, firstly a research methodology to determine which research approach to follow. Secondly, a literature review was then used to identify which HCI principles would be appropriate in the interface design of a web form for e-registration. The empirical part of this study consisted of a web form created according to these HCI principles, which was then evaluated according to usability goals. The evaluation included different data-gathering techniques, namely an observation of the manner in which the participants interacted with the web form, an interview which consisted of in-depth questions regarding the improvement of the web form and a questionnaire which consisted of specific questions regarding the usability of the web form. The web form was redesigned according to the suggestions made by the participants and a final web form prototype was introduced. Finally, recommendations were made for additional studies in order to extend the study of HCI principles application in web forms, specifically in the design of tax e-registration systems in South Africa. / Thesis (MSc (Computer Science))--North-West University, Vaal Triangle Campus, 2013

Ultrasound is a favorable tool for intra-operative surgical guidance due to its fast imaging speed and non-invasive nature. However, deformations of the anatomy caused by breathing, heartbeat, and movement of the patient make it difficult to track the location of anatomical landmarks during intra-operative ultrasound-guided interventions. While elastic registration can be used to compensate for image misalignment, its adaptation for clinical use has only been gradual due to the lack of standardized guidelines to quantify the performance of different registration techniques. Evaluation of elastic registration algorithms is a difficult task since the point to point correspondence between images is usually unknown. This poses a major challenge in the validation of non-rigid registration techniques for performance comparisons. Current validation guidelines for non-rigid registration algorithms exist for the comparison of techniques for magnetic resonance images of the brain. These frameworks provide users with standardized brain datasets and performance measures based on brain region alignment, intensity differences between images, and inverse consistency of transformations. These metrics may not all be suitable for ultrasound registration algorithms due to the different properties of the imaging modalities. Furthermore, other metrics are required for validating the registration performance on different anatomical images with large deformations such as the liver. This work presents a validation framework dedicated for ultrasound elastic registration algorithms. Quantitative validation metrics are evaluated for ultrasound images. These include a simulation technique to measure registration accuracy, a segmentation algorithm to extract anatomical landmarks to measure feature overlap, and a technique to measure the alignment of images using similarity metrics. An extensive study of an ultrasound temporal registration algorithm is conducted using the proposed validation framework. Experiments are performed on a large database of 2D and 3D US images of the carotid artery and the liver to assess the performance of this algorithm. In addition, two graphical user interfaces which integrate the image registration and segmentation techniques have been developed to visualize the performance of these algorithms on ultrasound images captured in real time. In the future, these interfaces may be used to enhance ultrasound examination. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-10-24 22:35:20.875

The aim of the research was: *to gain a better understanding on the concepts of Human-computer interaction (HCI) in general and the application of HCI principles in this field; to gain a better understanding of electronic registration systems (e-registration systems) and the use of web forms for this purpose; to gain a better understanding of which HCI principles could be applied to the design of a web form for e-registration; to apply the identified HCI principles to an example of a web form that was to be created; •to evaluate the design of the web form by means of different data-gathering techniques, and •to redesign the web form according to the data obtained from method triangulation. In order to achieve these objectives, the research used, firstly a research methodology to determine which research approach to follow. Secondly, a literature review was then used to identify which HCI principles would be appropriate in the interface design of a web form for e-registration. The empirical part of this study consisted of a web form created according to these HCI principles, which was then evaluated according to usability goals. The evaluation included different data-gathering techniques, namely an observation of the manner in which the participants interacted with the web form, an interview which consisted of in-depth questions regarding the improvement of the web form and a questionnaire which consisted of specific questions regarding the usability of the web form. The web form was redesigned according to the suggestions made by the participants and a final web form prototype was introduced. Finally, recommendations were made for additional studies in order to extend the study of HCI principles application in web forms, specifically in the design of tax e-registration systems in South Africa. / Thesis (MSc (Computer Science))--North-West University, Vaal Triangle Campus, 2013

Inaug.-Diss.--Cologne. / Vita. Bibliography: p. iii-ix.

Image registration is an important pre-processing operation to be performed before many image exploitation and processing functions such as data fusion, and super-resolution frame. Given two image frames, obtained from the same sensor or from different sensors, the registration problem involves determining the transformation that most nearly maps (or aligns) one image frame into the other. Typically, image registration requires intensive computational effort and the developed techniques are scene dependent. Furthermore, the problems of multimodal image registration (i.e. problem of registering images acquired from dissimilar sensors) and sub-pixel image registration (i.e. registering two images at sub-pixel accuracy) are highly challenging and no satisfactory solutions exist.This dissertation introduces novel techniques to solve the image registration problem both at the pixel-level and at the sub-pixel level. For pixel-level registration, a procedure is offered that enjoys the advantages that it is not scene dependent and provides the same level of accuracy for registering images acquired from different types of sensors. The new technique is based on obtaining the local frequency content of an image and using this local frequency representation to extract control points for establishing correspondence. To extract the local frequency representation of an image, a computationally efficient scheme based on minimizing the latency of a Gabor filter bank by exploiting certain biological considerations is presented. The dissertation also introduces an extension of using local frequency to solve the sub-pixel image registration problem. The new algorithm is based on using the scaled local frequency representation of the images to be registered, with computationally inexpensive scaling of the local frequency of the images prior to correlation matching. Finally, this dissertation provides a novel approach to solve the problem of multi-modal image registration. The principal idea behind this approach is to employ Computer Aided Design (CAD) models of man-made objects in the scene to permit extraction of regions-of-interest (ROI) whose local frequency representations are computed for extraction of stable matching points. Detailed performance evaluation results from an extensive set of experiments using diverse types of images are presented to highlight the strong points of the proposed registration algorithms.