Modern medicine has become reliant on medical imaging. Multiple modalities, e. g. magnetic resonance imaging (MRI), computed tomography (CT), etc. , are used to provide as much information about the patient as possible. The problem of geometrically aligning the resulting images is called image registration. Mutual information, an information theoretic similarity measure, allows for automated intermodal image registration algorithms. <br /><br /> In applications such as cancer therapy, diagnosticians are more concerned with the alignment of images over a region of interest such as a cancerous lesion, than over an entire image set. Attempts to register only the regions of interest, defined manually by diagnosticians, fail due to inaccurate mutual information estimation over the region of overlap of these small regions. <br /><br /> This thesis examines the region of union as an alternative to the region of overlap. We demonstrate that the region of union improves the accuracy and reliability of mutual information estimation over small regions. <br /><br /> We also present two new mutual information based similarity measures which allow for localized image registration by combining local and global image information. The new similarity measures are based on convex combinations of the information contained in the regions of interest and the information contained in the global images. <br /><br /> Preliminary results indicate that the proposed similarity measures are capable of localizing image registration. Experiments using medical images from computer tomography and positron emission tomography demonstrate the initial success of these measures. <br /><br /> Finally, in other applications, auto-detection of regions of interest may prove useful and would allow for fully automated localized image registration. We examine methods to automatically detect potential regions of interest based on local activity level and present some encouraging results.

Nonrigid image registration has received much attention in the medical imaging and computer vision research communities, because it enables a wide variety of applications. Feature tracking, segmentation, classification, temporal image differencing, tumour growth estimation, and pharmacokinetic modeling are examples of the many tasks that are enhanced by the use of aligned imagery. Over the years, the medical imaging and computer vision communties have developed and refined image registration techniques in parallel, often based on similar assumptions or underlying paradigms. This thesis focuses on variational registration, which comprises a subset of nonrigid image registration. It is divided into chapters that are based on fundamental aspects of the variational registration problem: image dissimilarity measures, changing overlap regions, regularizers, and computational solution strategies. Key contributions include the development of local versions of standard dissimilarity measures, the handling of changing overlap regions in a manner that is insensitive to the amount of non-interesting background information, the combination of two standard taxonomies of regularizers, and the generalization of solution techniques based on Fourier methods and the Demons algorithm for use with many regularizers. To illustrate and validate the various contributions, two sets of example imagery are used: 3D CT, MR, and PET images of the brain as well as 3D CT images of lung cancer patients.

Följande kandidatuppsats undersöker hur en elektronisk hälsoapplikation kan utformasför att öka medvetenheten om den personliga dagliga hälsan, fokuserat på huden och atthålla den frisk. Det sker genom att en prototyp har utformats där användaren genombilder samt text får instruktioner för att utföra en självkontroll. Prototypen innehållerockså en bildregistrering där användaren kan ladda upp bilder på en leverfläck ochgenom registreringen kan om leverfläcken utvecklas över tid. Syftet med prototypen äratt undersöka om en elektronisk hälsoapplikation utformad med fokus på återkopplingkan göra det möjligt för en person som inte är utbildad inom ämnet att undersöka sinhud samt se och följa förändring i en leverfläck genom bildanalys. Detta undersöktesgenom två tester. Ett frågeformulär där svarspersonen fick försöka avgöra om enleverfläck var frisk eller inte. Ett användartest där testpersonen fick testa bildanalysen,det som testades var om personen kunde ladda upp en bild samt se skillnad i bildernagenom bildregistreringen.Resultatet visar att majoriteten av enkätsvaren var korrekta svar, närmare bestämt 76,9procent. Personerna kunde identifiera om leverfläcken var frisk eller sjuk med hjälp avinformationen som tilldelades. Resultatet av användartesten visade att personerna kundeladda upp en bild på webbplatsen och sedan förstå bildanalysen. / This bachelor thesis examins how a electronic health application can be made toincrease awareness about personal daily health, with focus on individual skin andkeeping it healthy. This was made by creating a prototype where the user get usefulinformation on how to perform a self examination through text and images. Theprototype also contains functionality that allows the user to upload images of a moleand by an image registration follow possible changes over long periods of time. Thepurpose of the prototype is to investigate if an electronic health application with focuson feedback can make it possible for a person who is not educated in this area to examinthe skin and also discover possible changes over time with the image registration. Twotests were made to examin if this was possible. The first test was an questionnaire wherethe respondet tried to determine if a mole was healthy or not. The second test was a usertest where the test person got to try out the functionality with image registration in theprototype. The person got to upload an image and see the differences through the imageregistration.The results showed that the majority of the collected repsonses from the quetsionnairewas correct, with a percentage of 76,9 correct answers. The respondent could identify ifthe mole was healthy or not through the information that was presented. The results ofthe user test showed that all test persons could perform and understand the functionalityof uploading an image and then analyze the results throgh image registration.

Vitamin D is very important for endochondral ossification and it is commonly insufficient during pregnancy (Javaid et al., 2006). Insufficiency of vitamin D during pregnancy predicts bone mass and hence predicts adult osteoporosis (Javaid et al., 2006). The relationship between maternal vitamin D and manually measured fetal biometry has been studied (Mahon et al., 2009). However, manual fetal biometry especially volumetric measurements are subjective, time-consuming and possibly irreproducible. Computerised measurements can overcome or at least reduce such problems. This thesis concerns the development and evaluation of novel methods to do this. This thesis makes three contributions. Firstly, we have developed a novel technique based on the Random Forests (RF) classifier to segment and measure several fetal femoral characteristics from 3D ultrasound volumes automatically. We propose a feature selection step in the training stage to eliminate irrelevant features and utilise the "good" ones. We also develop a weighted voting mechanism to weight tree probabilistic decisions in the RF classifier. We show that the new RF classifier is more accurate than the classic method (Yaqub et al., 2010b, Yaqub et al., 2011b). We achieved 83% segmentation precision using the proposed technique compared to manually segmented volumes. The proposed segmentation technique was also validated on segmenting adult brain structures in MR images and it showed excellent accuracy. The second contribution is a wavelet-based image fusion technique to enhance the quality of the fetal femur and to compensate for missing information in one volume due to signal attenuation and acoustic shadowing. We show that using image fusion to increase the image quality of ultrasound images of bony structures leads to a more accurate and reproducible assessment and measurement qualitatively and quantitatively (Yaqub et al., 2010a, Yaqub et al., 2011a). The third contribution concerns the analysis of data from a cohort study of 450 fetal femoral ultrasound volumes (18-21 week gestation). The femur length, cross-sectional areas, volume, splaying indices and angles were automatically measured using the RF method. The relationship between these measurements and the fetal gestational age and maternal vitamin D was investigated. Segmentation of a fetal femur is fast (2.3s/volume), thanks to the parallel implementation. The femur volume, length, splaying index were found to significantly correlate with fetal gestational age. Furthermore, significant correlations between the automatic measurements and 10 nmol increment in maternal 25OHD during second trimester were found.

Multi-modal image fusion is an active research area with many civilian and military applications. Fusion is defined as strategic combination of information collected by various sensors from different locations or different types in order to obtain a better understanding of an observed scene or situation. Fusion of multi-modal images cannot be completed unless these two modalities are spatially aligned. In this research, I consider two important problems. Multi-modal, multi-perspective image registration and decision level fusion of multi-modal images. In particular, LiDAR and visual imagery. Multi-modal image registration is a difficult task due to the different semantic interpretation of features extracted from each modality. This problem is decoupled into three sub-problems. The first step is identification and extraction of common features. The second step is the determination of corresponding points. The third step consists of determining the registration transformation parameters. Traditional registration methods use low level features such as lines and corners. Using these features require an extensive optimization search in order to determine the corresponding points. Many methods use global positioning systems (GPS), and a calibrated camera in order to obtain an initial estimate of the camera parameters. The advantages of our work over the previous works are the following. First, I used high level-features, which significantly reduce the search space for the optimization process. Second, the determination of corresponding points is modeled as an assignment problem between a small numbers of objects. On the other side, fusing LiDAR and visual images is beneficial, due to the different and rich characteristics of both modalities. LiDAR data contain 3D information, while images contain visual information. Developing a fusion technique that uses the characteristics of both modalities is very important. I establish a decision-level fusion technique using manifold models.

In radiation therapy, it is imperative to deliver high doses of radiation to the tumor while reducing radiation to the healthy tissue. Respiratory motion is the most significant source of errors during treatment. Therefore, it is essential to accurately model respiratory motion for precise and effective radiation delivery. Many approaches exist to account for respiratory motion, such as controlled breath hold and respiratory gating, and they have been relatively successful. They still present many drawbacks. Thus, research has been expanded to tumor tracking. The overall goal of 4D-CT is to predict tumor motion in real time, and this work attempts to move in that direction. The following work addresses both the temporal and the spatial aspects of four-dimensional CT reconstruction. The aims of the paper are to (1) estimate the temporal parameters of 4D models for anatomy deformation using a novel neural network approach and (2) to use intelligently chosen non-uniform, non-separable splines to improve the spatial resolution of the deformation models in image registration.

Legal regulation of the Commercial Register The purpose of my master's thesis is to describe the Commercial Register legislation in the Czech Republic, including both a development of the Commercial Register and its current legal framework, with regard to a recent recodification of private law which came into effect on January 1, 2014. The thesis is composed of 8 chapters. Chapter One summarizes a legislation development of the Commercial Register in Czech countries since the Austria-Hungary period through the changes of a legal system after 1989 to a current legislation after recodification. Chapter Two deals with a term and a nature of the Public Registers of Legal Entities and Natural Persons, on which all of the elemental principles of the Commercial Register are explained, when the Commercial Register had become one of the types of public registers. Subchapter about courts maintaining the Commercial Register contains an analysis of their operations. Subchapter about persons and entries that can be entered into public registers defines essential facts, which shall be entered into the register. Chapter Three explores the Commercial Register, its individual units and facts which can enter those units. It is necessary to keep the legislation generality of public registers in mind, to which a...

V první části se práce se zabývá rešerší metod a principů potřebných při registraci obrazu. Dále pak popisuje zobrazovací systémy očního pozadí jako jsou OCT, fundus kamera a SLO. Druhá část práce je zaměřena na praktickou realizaci programů pro registraci snímků z OCT, SLO a fundus kamery v programovém prostředí Matlab.

This document deals with the pre-processing and the segmentation of human vertebrae from computed tomography 3D image data. It describes image registration and segmentation methods concretely and commonly used in image data processing during the automated spine canal localization process and the localization of each vertebrae centroid. The 3D deformable model development is described in the work together with the introduction to the previous state of art and the progress of vertebrae segmentation using 3D deformable models registration. This work presents the evaluation of the accuracy and the reliability from the segmentation and localization results.

This thesis is devoted to groups as value added tax payers. This concept was introduced into Czech law on 1st January 2008. A VAT group enables persons that meet the criteria required by the VAT Act to be considered a single taxable person, i.e. a single tax payer. The Czech VAT group legislation is based on article 11 of Council Directive 2006/112/EC of 28 November 2006 on the common system of value added tax. The aim of this thesis is to present and thoroughly analyze VAT group legislation in Czech law, and to point out certain pitfalls of this legislation, including its interaction with EU law, and the law of some of the other EU member states. A secondary goal is to assess the rate at which VAT groups are being used in the Czech Republic. The first chapter describes VAT group in EU law, and its introduction into the Czech legal order. The second chapter discusses the requirements that the law puts on members of a VAT group, with extra emphasis on the requirement of close binding of persons, including the membership of physical persons and non-taxable persons in a VAT group. The third chapter deals with VAT group as a subject of legal relations, describing in more detail the concept of a representative member and the responsibilities of a VAT group member. The next chapter takes a more practical...