Image-guided neurosurgery interventions are becoming sur- gical procedure routines. We suggest a novel method for automatic marker localization in X-ray images for Leksell SurgiPlan® which is an image-based neurosergical treat- ment planning software provided by Elekta Instrument AB. We implemented an algorithm for fiducial marker localiza- tion based on feature detection, classification and prior geo- metrical knowledge of the markers. Automatic localization ca help to decrease the human error associated with manual registration of these fiducial markers which is the current applied method for X-ray images in Leksell SurgiPlan®.

Con el transcurrir del tiempo, las transacciones vehiculares a través de la compra-venta se han vuelto más frecuentes y sencillas, a su vez segura, pues los propietarios registran estas transacciones en el Registro de Propiedad Vehicular para obtener la seguridad jurídica. A la par de este hecho, surge también la conducta preventiva de los propietarios de los vehículos que deciden comprar una Póliza de seguro vehicular para proteger su unidad frente a los riesgos que se puedan presentar. Si bien el propietario ha sido diligente en inscribir la transferencia vehicular y asegurar su unidad ante un eventual siniestro, hemos identificado, dos desventajas para el asegurado/propietario: (i) Este puede adquirir un bien sin conocer que el costo de la unidad ha sido cuantificada como cero, pues fue declarado como pérdida total por una compañía aseguradora, de lo cual no se tiene conocimiento debido a que no contamos con esa información de forma accesible, y (ii) De existir un siniestro la aseguradora rechazaría la cobertura por aplicación Cláusula de Exclusión expresa o por Declaración reticente o falsa, En el presente trabajo, proponemos como solución al problema la incorporación al Registro de Propiedad Vehicular de los Registros Públicos, la Obligación de las Aseguradoras de reportar la pérdida total del vehículo de tal forma que el registrador la pueda considerar como parte de la publicidad de las características de las unidades. / Over time, vehicle transactions through purchase and sale have become more frequent and simple, and at the same time safe, because the owners register these transactions in the Vehicle Property Registry to obtain legal security. At the same time, the preventive behavior of the owners who decide to buy a vehicle insurance policy to protect their unit against the risks. Although the owner has been diligent in registering the vehicle transfer and insuring his unit in the event of a loss, we have identified two disadvantages for the insured/owner: (i) The owner can acquire a property without knowing that the cost of the unit has been quantified as zero, since it was declared a total loss by an insurance company, of which we have no knowledge due to the fact that we do not have that information in an accessible manner, and (ii) If there is a claim, the insurance company would reject the coverage due to the application of an express Exclusion Clause or a reluctant or false statement. In the present work, we propose as a solution to the problem, the incorporation to the Registry of Vehicle Property of the Public Registries, the Obligation of the Insurers to report the total loss of the vehicle in such a way the person who registers, can consider it as part of the publicity of the characteristics of the units. / Trabajo de investigación

>Magister Scientiae - MSc / Nanomedicines are loosely defined as medicines that seek to apply nanotechnology. Currently, nanomedicines are available for clinical use, including treatments for cancer, high cholesterol, hepatitis, COVID-19 vaccination, among other uses (Patra et al., 2018; Gao et al., 2021). Most of the nanomedicines meet the definition of medicines according to various national legislations. Consequently, these products are regulated as medicines. Nanomedicines present major differences in biological details and increased complexity of clinical use. They integrate different technology subsets from therapeutics to imaging and integrated non-invasive diagnosis (Gaspar, 2007). These complexities require extra regulatory effort.

This thesis tackles the challenge of registering modern to historic images in the context of urban rephotography. It aims at automatically identifying stable image features in scenes, which have been exposed to medium to tremendous changes across the years. Instead, the related field of location recognition mainly focuses on illumination and seasonal changes. This work illustrates that common feature descriptors are applicable in the context of historic and modern image matching, while local detectors are not, but most important is the choice of appropriate correspondence filters. It is verified that major structural changes are most challenging for traditional image matching approaches and the methods developed in this work are applicable to challenging image pairs beyond rephotography. Besides, features extracted from Convolutional Neural Networks (CNNs), originally trained for the task of location recognition, show high performance and should be further developed for the specific task of historic to modern image matching. At last, practical developments are presented, including an online portal for presenting and organizing rephotographs as well as an initial version of a mobile application, which supports recovering the original viewpoint of an image.

The state of Maryland has been unsuccessful in achieving its goal of registering all of its population as organ donors. The purpose of this correlational study was to understand if allowing registered donors to remain anonymous would increase donor registration rates. The theoretical foundation of this study was the theory of planned behavior. Data were collected from the Motor Vehicle Administration of Maryland and the Division of Motor Vehicle of Virginia. The data were analyzed using regression displacement, interrupted time series analysis, auto correlation analysis, and Arima Box Jenkins methodology. According to the study findings, offering the option to remain anonymous and registering to be an organ donor with no heart icon on the driver's license did not have the immediate effect of encouraging more people to register as an organ donor. Parameter estimates from an Arima autoregression analysis did suggest that the impact of the removal of the heart icon may have a delayed impact, although data availability limited attempts at further investigation.

Background: Internationally educated nurses (IENs) have become a significant source of nursing supply as a result of nursing workforce shortages, the aging population and patient acuity. However, IENs face substantial delays and barriers obtaining licensure and employment equivalent to their skills and experience. When IENs are unable to practice their profession, they experience a considerable loss of professional identity, earning potential and financial stability. The purpose of this scoping review was to identify and map key themes in the existing literature on the barriers and strategies to timely nursing registration for IENs. Methods: Arksey and O’Malley’s methodological framework was used for this study. Seven electronic databases were searched along with several grey literature sources in order to capture articles that discussed barriers and strategies to timely nursing registration for IENs. A numerical and thematic analysis was conducted to explore the scope of the literature and to present the findings. Results: After full-text screening, 38 pieces of relevant literature were selected for inclusion in the review. The majority (53%) were studies and most (42%) were qualitative. Seven key themes emerged from the thematic analysis: timely information, credential assessment, obtaining documents, language requirements, nursing registration costs, bridging programs and the nursing registration exam. Conclusion: While some IENs are able to successfully navigate the process for obtaining nursing licensure, it is clear that many IENs face obstacles at every step of the process and some never become registered as nurses. Further research is required about whether the various bridging programs and initiatives meet the needs of IENs and help them become registered as nurses. Findings from this scoping review have significant implications for nurse staffing and policies and practices to improve the strength, stability, and diversity of the nursing workforce. / Thesis / Master of Science in Nursing (MSN) / This study explores the literature on internationally educated nurses (IENs) and the difficulties they face, as well as the strategies they use to obtain nursing registration. Arksey and O’Malley’s framework was used to guide this scoping review. Seven databases were searched along with many grey literature sources in order to find articles on barriers and strategies to nursing registration for IENs. A numerical and thematic analysis was conducted to present the findings. Seven main themes emerged from the thematic analysis: timely information, credential assessment, obtaining documents, language requirements, nursing registration costs, bridging programs and the nursing registration exam. More research is required about whether the various bridging programs and initiatives meet the needs of IENs and help them become registered as nurses. Findings from this study are important for nurse staffing and policies and practices to improve the stability and diversity of the nursing workforce.

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With advancements in space technology, remote sensing applications, and computer vision, significant improvements in the data describing our planet are seen today. Researchers want to gather different kinds of data and perform data fusion techniques between them to increase our understanding of the world. Two such data types are Electro-Optical images and Synthetic Aperture Radar images. For data fusion, the images need to be accurately aligned. Researchers have investigated methods for robustly and accurately registering these images for many years. However, recent advancements in imaging systems have made the problem more complex than ever. Currently, the imaging satellites that capture information around the globe have achieved a resolution of less than a meter per pixel. There is an increase in signal complexity for high-resolution SAR images due to how the imaging system operates. Interference between waves gives rise to speckled noise and geometric distortions, making the images very difficult to interpret. This directly affects the image registration accuracy. In this thesis, the complexity of the problem regarding registration between SAR and EO data was described, and methods for registering the images were investigated. The methods were feature- and area-based. The feature-based method used a KAZE filter and SURF descriptor. The method found many key points but few correct correspondences. The area-based methods used FFT and MI, respectively. FFT was deemed best for higher quality images, whereas MI better dealt with the non-linear intensity difference. More complex techniques, such as dense neural networks, were excluded. No method achieved satisfying results on the entire data set, but the area-based methods accomplished complementary results. A conclusion was drawn that the distortions in the SAR images are too significant to register accurately using only CV algorithms. Since the area-based methods achieved good results on images excluding significant distortions, future work should focus on solving the geometrical errors and increasing the registration accuracy

This thesis deals with image registration of MRI images using neural networks. Image registration combines multiple images of the same subject that were taken at different points in time, from different sensors, or from different points of views into a single image and coordinate system. Image registration is widely used in medical imaging and remote sensing. In this thesis feed forward neural networks and wavelet neural networks are used to estimate the parameters of registration. Simulations show that the wavelet networks provide significantly more accurate results than feed forward networks and other proposed methods including genetic algorithms. Both methods are also shown to be robust to noise and changes in parameter ranges.

Yes / Point set registration has been actively studied in computer vision and graphics. Optimization algorithms are at the core of solving registration problems. Traditional optimization approaches are mainly based on the gradient of objective functions. The derivation of objective functions makes it challenging to find optimal solutions for complex optimization models, especially for those applications where accuracy is critical. Learning-based optimization is a novel approach to address this problem, which learns the gradient direction from datasets. However, many learning-based optimization algorithms learn gradient directions via a single feature extracted from the dataset, which will cause the updating direction to be vulnerable to perturbations around the data, thus falling into a bad stationary point. This paper proposes the General Discriminative Optimization (GDO) method that updates a gradient path automatically through the trade-off among contributions of different features on updating gradients. We illustrate the benefits of GDO with tasks of 3D point set registrations and show that GDO outperforms the state-of-the-art registration methods in terms of accuracy and robustness to perturbations.