Dissertations / Theses on the topic 'Registration'
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Purwani, Sri. "Ensemble registration : combining groupwise registration and segmentation." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/ensemble-registration-combining-groupwise-registration-and-segmentation(5f3c06b4-4909-492b-bbc9-a0fecb77d216).html.
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Registration of a group of images generally only gives a pointwise, dense correspondence defined over the whole image plane or volume, without having any specific description of any common structure that exists in every image. Furthermore, identifying tissue classes and structures that are significant across the group is often required for analysis, as well as the correspondence. The overall aim is instead to perform registration, segmentation, and modelling simultaneously, so that the registration can assist the segmentation, and vice versa. However, structural information does play a role in conventional registration, in that if the registration is successful, it would be expected structures to be aligned to some extent. Hence, we perform initial experiments to investigate whether there is explicit structural information present in the shape of the registration objective function about the optimum. We perturbed one image locally with a diffeomorphism, and found interesting structure in the shape of the quality of fit function. Then, we proceed to add explicit structural information into registration framework, using various types of structural information derived from the original intensity images. For the case of MR brain images, we augment each intensity image with its own set of tissue fraction images, plus intensity gradient images, which form an image ensemble for each example. Then, we perform groupwise registration by using these ensembles of images. We apply the method to four different real-world datasets, for which ground-truth annotation is available. It is shown that the method can give a greater than 25% improvement on the three difficult datasets, when compared to using intensity-based registration alone. On the easier dataset, it improves upon intensity-based registration, and achieves results comparable with the previous method.
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Schestowitz, Samuel. "Unifying models and registration : a framework for model-based registration and non-rigid registration assessment." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.509887.
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Prasai, Persis. "Multimodality image registration." Birmingham, Ala. : University of Alabama at Birmingham, 2006. http://www.mhsl.uab.edu/dt/2007m/prasai.pdf.
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Participants, All. "Breakfast and Registration." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/dcseug/2018/schedule/12.
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Cole, Jeffrey Bryan. "Voter Registration Made Easy: Who Takes Advantage of Election Day Registration and Same Day Registration and Do They Vote?" The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354509669.
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Müller, Barbara K. "Multinational trademark registration systems : international trademark registration today and in the future /." Bern : Stämpfli, 2002. http://www.gbv.de/dms/spk/sbb/recht/toc/349360197.pdf.
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Li, Lin. "Multi-scale spectral embedding representation registration (MSERg) for multi-modal imaging registration." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1467902012.
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Batlle, Subirós Elisabet. "Large-Scale Surface registration." Doctoral thesis, Universitat de Girona, 2008. http://hdl.handle.net/10803/7606.
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The first part of this work presents an accurate analysis of the most relevant 3D registration techniques, including initial pose estimation, pairwise registration and multiview registration strategies. A new classification has been proposed, based on both the applications and the approach of the methods that have been discussed.The main contribution of this thesis is the proposal of a new 3D multiview registration strategy. The proposed approach detects revisited regions obtaining cycles of views that are used to reduce the inaccuracies that may exist in the final model due to error propagation. The method takes advantage of both global and local information of the registration process, using graph theory techniques in order correlate multiple views and minimize the propagated error by registering the views in an optimal way. The proposed method has been tested using both synthetic and real data, in order to show and study its behavior and demonstrate its reliability.
La primera part d'aquest treball presenta una anàlisi acurada de les tècniques de registre 3D es rellevants, incloent tècniques d'estimació de la posició inicial, registre pairwise i registre entre múltiples vistes. S'ha proposat una nova classificació de les tècniques, depenent de les seves aplicacions i de l'estratègia utilitzada.
La contribució mes important d'aquesta tesi és la proposta d'un nou mètode de registre 3D utilitzant múltiples vistes. El mètode proposat detecta regions ja visitades prèviament, obtenint cicles de vistes que s'utilitzen per tal de reduir els desalineaments en el model final deguts principalment a la propagació de l'error durant el procés de registre. Aquest mètode utilitza tant informació global com local, correlacionant les vistes mitjançant tècniques de grafs que permeten minimitzar l'error propagat i registrar les vistes de forma òptima. El mètode proposat ha estat provat utilitzant dades sintètiques i reals, per tal de mostrar i analitzar el seu comportament i demostrar la seva eficàcia.
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Harg, Erik. "Volume-to-volume registration." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9196.
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Implementation of automated volume-to-volume registration applications for three separate registration steps desired in enhancing neurosurgical navigation is considered. Prototype implementations for MRI-to-MRI registration, MRI-to-US registration and US-to-US registration have been made using registration methods available in the Insight Toolkit, with variants of the Mutual Information similarity metric. The obtained results indicate that automatic volume-to-volume registration using Normalized Mutual Information should be feasible for the neuronavigational applications considered here, with sufficient accuracy.
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Wyatt, Paul. "Concurrent segmentation and registration." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398273.
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Wei, YaNing. "Image registration and matching." Thesis, University of Nottingham, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.430757.
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Habboush, Isam H. (Isam Hussein). "Image registration and fusion." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/37009.
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Yanovsky, Igor. "Unbiased nonlinear image registration." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1619485511&sid=16&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Rohrer, Jonathan. "Accelerated nonrigid image registration." Berlin dissertation.de, 2009. http://d-nb.info/999883968/04.
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Wang, Xuetao. "Olympiad delegation registration system." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2551.
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The purpose of this project is to design, build and implement a web application system for the Olympiad delegation registration. All the pages and user registration information will be stored in a PostgreSQL database and retrieved by JAVA Servlet and JDBC (JAVA Database Connectivity). The main purpose of this project is to provide an easy-to-register and web-base communication evironment for the National Olympic Committes (NOC) and the Organizing Committee for the Olympic Games (OCOG).
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FONTANA, SIMONE. "Robust Point Clouds Registration." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/180707.
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L’allineamento di Point Cloud (nuvole di punti) è un problema attuale e molto studiato, per il quale esistono molte soluzioni efficaci. Non di meno, gli approcci presenti in letteratura fanno affidamento su una buona inizializzazione e su un set di parametri adeguato. Questi approcci potrebbero venir divisi in due categorie: quelli basati sulle feature e quelli basati sulla distanza tra punti. Gli approcci che ricadono nella prima categoria, di solito, allineano due point cloud sfruttando dei punti salienti, keypoints, e un qualche tipo di descrittore, nello stesso modo che viene di solito usato con le immagini 2D.
Gli approcci appartenenti alla seconda categoria, invece, non calcolano esplicitamente nessuna corrispondenza, ma queste vengono approssimate utilizzando il punto più vicino, senza la necessità di calcolare alcuna feature. L'algoritmo più importante in questa categoria è Iterative Closest Point (ICP). La maggior parte degli altri algoritmi, infatti, è una variante di ICP e lo stesso vale per uno degli approcci qui proposti.
In questo lavoro introduciamo due nuove tecniche.
La prima è una variante di ICP con una differente data association, basata su un modello probabilistico. Benché sia nata con l’obiettivo di allineare una point cloud molto sparsa, con una densa, ha dimostrato di essere capace di ottenere risultati qualitativamente migliori degli altri approcci anche su problemi di allineamento classici. Di notevole importanza, inoltre, è la sua bassa sensibilità ai parametri, un problema che, al contrario, affligge molti lavori presenti nella letteratura, come mostreremo, e che ne limita il loro utilizzo nel campo della robotica.
Il secondo algoritmo da noi ideato è volto all’allineamento di due point cloud, senza la necessità di fornire alcuna stima iniziale sul loro allineamento. Questo è un vantaggio molto importante rispetto alle altre tecniche descritte nella letteratura. Mentre quelle basate su feature, benché siano in grado di allineare due nuvole di punti globalmente, senza necessità di una stima iniziale, non sono applicabili a point cloud sparse (uno dei casi che abbiamo dovuto affrontare durante questo lavoro), quelle basate su ICP hanno necessariamente bisogno di una stima iniziale adeguata, altrimenti convergeranno ad una soluzione sbagliata.
L’approccio da noi utilizzato combina i vantaggi di entrambe le tecniche. E’ infatti applicabile ad ogni point cloud, indipendentemente dalla possibilità di estrarne feature, ma allo stesso tempo non ha bisogno di una stima iniziale. Per ottenere ciò abbiamo sfruttato un famoso algoritmo di ottimizzazione, Particle Swarm Optimization, che, benché non dia alcuna garanzia di convergenza ad un ottimo globale, in pratica ha mostrato una buona abilità nello uscire dagli ottimi locali, dove invece molti altri algoritmi rimangono intrappolati.Point clouds registration is a very well studied problem, with many different and efficient solutions. Nevertheless, the approaches in the literature rely heavily on a good initialization and on a good set of parameters. These approaches could be roughly divided into two categories: those based on features and the so-called closest-point-based. The first category aims at aligning two point clouds by first detecting some salient points, the keypoints, and calculating their descriptors so that they can be compared, in the same way it is usually done with 2D images. On the other hand, the latter category approximates correspondences by iteratively choosing the closest point, without the need for any kind of feature. The most important algorithm in this category is Iterative Closest Point (ICP). Most other algorithms are variants of ICP, so is one of the proposed approaches. In this work we introduce two novel solutions to point clouds registration. The first one is a variant of ICP, with a different data association, derived from a probabilistic model. The experiments show that is very effective at aligning a sparse point cloud with a dense one, one of the issues we had to face during this work. On the other hand, it showed very good results also on standard alignment problems, often better than other popular state of the art algorithms. We show that, for the most common approaches, the quality of the result is heavily dependent on some parameters that, thus, need to be carefully calibrated before the algorithms could be used in real applications. Moreover, a new calibration is usually required when facing a new scenario. For this reasons we propose this innovative technique, that aims, besides at being capable of aligning two generic point clouds, independently from their density, at being more robust w.r.t. wrong parameter sets. The second technique we developed is a global point cloud registration algorithm. ICP-like techniques requires, in order to converge to the right solution, an initial estimate of the transformation between the two point clouds. Without a proper initial guess, the algorithm will probably remain stuck in a local minima. On the other hand, feature-based techniques do not require any initial estimate but are not applicable to sparse point clouds, because they do not contain enough information to extract meaningful descriptors. The approach we developed combines the advantages of both approaches. It is based on a soft-computing technique, Particle Swarm Optimization, that is known for being able to escape from local optima. The result is an algorithm capable of aligning any kind of point cloud, without the need of any initial estimate of the transformation.
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Rohde, Gustavo Kunde. "Registration methods for quantitative imaging." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2938.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.Thesis research directed by: Applied Mathematics and Scientific Computation. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Augdal, Sigmund. "Surface-based Markerless Patient Registration." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9200.
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When doing image guided surgery, it is important to find a proper alig nment of the coordinate systems for the images and for the tracking system that tracks the positions o f the surgeons tools. This report explores surface based methods for finding such an alignment, using either an optical shape measurement device, or surfaces gathered by passing the tracking tool along the surface of the patien t. Accuracy and usability factors are explored, and compared to existing methods based on finding corresponding points
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Aravalli, Koushik V. "Registration with Graphical Processor Unit." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1202409849/.
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Nguyen, Tam M. "Vergence registration in the dark /." Adobe Acrobat Reader required to view document, 2007. http://library.neco.edu/theses/NguyenThesisDec07.pdf.
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Stehn, Fabian [Verfasser]. "Geometric hybrid registration / Fabian Stehn." Berlin : Freie Universität Berlin, 2011. http://d-nb.info/1025169042/34.
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Bagci, Ulas. "Automatic anatomy recognition and registration." Thesis, University of Nottingham, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.537679.
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Sheward, Louisa. "The path to nurse registration." Thesis, University of Strathclyde, 2005. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21626.
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The aim of this study was to identify the factors promoting or impeding pre-registration degree level education at the first School of Nursing offering transfer from diploma to degree programmes. A quantitative approach was used to collect data from student nurses using a questionnaire. This included an attitude towards obtaining a degree scale developed using psychometric tests to maximise reliability and validity. The remainder of the questionnaire consisted of checklists of the factors influencing the decision to accept transfer or not and demographic information. In the main study the questionnaire was distributed to 113 third year adult branch student nurses. The response rate was 93%. The 105 participants were typical of student nurses, i. e. the majority were female, mature and worked part-time. Attitudes towards obtaining a degree were generally positive. The majority of students believed obtaining a degree will help nurses develop their career and increase professional status. However, the majority disagreed that obtaining a degree is essential to be a good nurse, will make nurses better at their jobs and will improve the patient care provided by nurses. Only 25% believed obtaining a degree ought to be essential for all student nurses. Twenty nine students did not accept transfer to the degree. Of these 79% reported this was due to the combined pressures of academic workload, family and work. None of these participants believed that obtaining a degree will make nurses better at theirJobs. A theory-practice divide seemed to exist, whereby many of the participants did not relate the increased degree knowledge with clinical practice. Based on this study's limited evidence, achieving an all graduate profession at the point of registration appears difficult because of students' limited abilities and motivation to obtain a degree. Possible solutions include to narrow the entrance gates or to achieve an all graduate profession after registration by implementing short-term learning contracts for newly qualified nurses. Understanding which types of students accept or decline transfer could be better understood by improved information systems.
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Bird, Joshua Campbell Cater. "Evaluation of Deformable Image Registration." Thesis, University of Canterbury. Physics, 2015. http://hdl.handle.net/10092/10577.
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Deformable image registration (DIR) is a type of registration that calculates a deformable vector field (DVF) between two image data sets and permits contour and dose propagation. However the calculation of a DVF is considered an ill-posed problem, as there is no exact solution to a deformation problem, therefore all DVFs calculated contain errors. As a result it is important to evaluate and assess the accuracy and limitations of any DIR algorithm intended for clinical use. The influence of image quality on the DIR algorithms performance was also evaluated.
The hybrid DIR algorithm in RayStation 4.0.1.4 was assessed using a number of evaluation methods and data. The evaluation methods were point of interest (POI) propagation, contour propagation and dose measurements. The data types used were phantom and patient data. A number of metrics were used for quantitative analysis and visual inspection was used for qualitative analysis.
The quantitative and qualitative results indicated that all DVFs calculated by the DIR algorithm contained errors which translated into errors in the propagated contours and propagated dose. The results showed that the errors were largest for small contour volumes (<20cm3) and for large anatomical volume changes between the image sets, which pushes the algorithms ability to deform, a significant decrease in accuracy was observed for anatomical volume changes of greater than 10%. When the propagated contours in the head and neck were used for planning the errors in the DVF were found to cause under dosing to the target tumour by up to 32% and over dosing to the organs at risk (OAR) by up to 12% which is clinically significant. The results also indicated that the image quality does not have a significant effect on the DIR algorithms calculations. Dose measurements indicated errors in the DVF calculations that could potentially be clinically significant. The results indicate that contour propagation and dose propagation must be used with caution if clinical use is intended. For clinical use contour propagation requires evaluation of every propagated contour by an expert user and dose propagation requires thorough evaluation of the DVF.
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Henson, Benjamin. "Image registration for sonar applications." Thesis, University of York, 2017. http://etheses.whiterose.ac.uk/19536/.
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This work develops techniques to estimate the motion of an underwater platform by processing data from an on-board sonar, such as a Forward Looking Sonar (FLS). Based on image registration, a universal algorithm has been developed and validated with in field datasets. The proposed algorithm gives a high quality registration to a fine (sub-pixel) precision using an adaptive filter and is suitable for both optical and acoustic images. The efficiency and quality of the result can be improved if an initial estimate of the motion is made. Therefore, a coarse (pixel-wide) registration algorithm is proposed, this is based on the assumption of local sparsity in the pixel motion between two images. Using a coarse and then fine registration, large displacements can be accommodated with a result that is to a sub-pixel precision. The registration process produces a displacement map (DM) between two images. From a sequence of DMs, an estimation of the sensor's motion is made. This is performed by a proposed fast searching and matching technique applied to a library of modelled DMs. Further, this technique exploits regularised splines to estimate the attitude and trajectory of the platform. To validate the results, a mosaic has been produced from three sets of in field data. Using a more detailed model of the acoustic propagation has the potential to improve the results further. As a step towards this a baseband underwater channel model has been developed. A physics simulator is used to characterise the channel at waymark points in a changing environment. A baseband equivalent representation of the time varying channel is then interpolated from these points. Processing in the baseband reduces the sample rate and hence reduces the run time for the model. A comparison to a more established channel model has been made to validate the results.
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Wagener, Dirk Wolfram. "Feature tracking and pattern registration." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53424.
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Thesis (MScEng) -- Stellenbosch University, 2003.ENGLISH ABSTRACT: The video-based computer vision patient positioning system that is being developed at iThemba Laboratories, relies on the accurate, robust location, identification and tracking of a number of markers on the patient's mask. The precision requirements are demanding - a small error in the location of the markers leads to an inaccurate positioning of the patient, which could have fatal consequences. In this thesis we discuss the contsruction of suitable markers, their identification with subpixel accuracy, as well as a robust tracking algorithm. The algorithms were implemented and tested on real data. We also note and give examples of other applications, most notably 2D human face tracking and the 3D tracking of a moving person.
AFRIKAANSE OPSOMMING: Die video-gebaseerde rekenaarvisie pasiënt posisionerings stelsel wat by iThemba Laboratoriums ontwikkel word, maak staat op die akkurate opsporing, identifikasie en volging van 'n stel merkers op die pasiënt se masker. Die akkuraatheids voorwaardes is besonders streng - selfs 'n klein fout in die lokasie vandie merkers sal lei tot die onakkurate posisionering van die pasiënt, wat dodelike gevolge kan hê. In hierdie tesis bespreek ons die konstruksie van geskikte merkers, die identifikasie van die merkers tot op subbeeldingselement vlak en ook die akkurate volging van die merkers. Die algoritmes is op regte data getoets. Ander toepassings soos 2D en 3D menlike gesigs-volging word ook kortliks bespreek.
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Fitch, Alistair John. "Fast statistically robust image registration." Thesis, University of Surrey, 2003. http://epubs.surrey.ac.uk/844612/.
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Image registration is the automatic alignment of images. It is a fundamental task in computer vision. Image registration is challenging, in part, because of the wide range of applications with an equally wide range of content. Applications that require the automatic alignment of images include: super-resolution, face detection, video coding, medical imaging, mosaicking, post-production video effects, and satellite image registration. The wide and diverse range of applications have led to a wide and diverse range of image registration algorithms. An image registration algorithm is defined by its transformation, criterion, and search. The transformation is the model of image deformation required for alignment. The criterion is the definition of the best registration. The search describes how the best registration is to be found. This thesis presents two image registration methods; fast robust correlation and orientation correlation. The presented methods find translational transformations. Both define their criterion of the best registration using robust statistics. Fast robust correlation applies robust statistics to pixel intensity differences. Orientation correlation applies robust statistics to differences in orientation of intensity gradient. This gives orientation correlation the property of illumination invariance. Both use an exhaustive search to find the best registration. The novelty of fast robust correlation and orientation correlation is the combination of robust statistics, with an exhaustive search that can be computed quickly with fast Fourier transforms (FFTs). This is achieved by expressing a statistically robust registration surface with correlations. The correlations are computed quickly using FFTs. Computation with FFTs is shown to be particularly advantageous in registration of large images of similar size. Experimental comparisons demonstrate the advantages of the methods over standard correlation-based approaches. Advantage is shown in the experiments of: video coding, video frame registration, tolerance of rotation and zoom, registration of multimodal microscopy images, and face registration.
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FEI, Baowei. "Image Registration for the Prostate." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1224274091.
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Paquin, Dana. "Multiscale methods for image registration /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
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Hunt, Jeff K. Hung John Y. McDonald Timothy P. "Pine seedling detection and registration." Auburn, Ala., 2009. http://hdl.handle.net/10415/1959.
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Tobin, Brendan. "Automatic Registration of Multispectral Images." Thesis, The University of Arizona, 2013. http://hdl.handle.net/10150/297771.
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Multispectral imaging is an important tool in art conservation because it allows researchers to view under-drawing and restoration efforts on a painting. It is necessary to precisely align various images of the same painting using digital image processing techniques, however this is complicated by inconsistencies in image contents and the use of multiple cameras. This paper seeks to develop an effective method to automatically align and rescale multispectral images of paintings. Key point identification using the Speeded-Up Robust Feature detection algorithm with refinement by Random Sample Consensus fitting was determined to be an accurate and efficient method for aligning visible and infrared multispectral images.
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Pourmoshir, Shirin. "An Aerial Image Registration Tool." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372091.
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GeoMemories is a project that aims to digitalize the historical aerial photograph archives of the Aerofototeca Nazionale in Rome. In order to use those photographs in GeoMemories, there is a need to have an application to help with producing better photographs. This study presents different steps of creating this aerial image registration application or what is called GeoImage. GeoImage is a desktop application which is intended to give researchers opportunities to work on aerial historical images easie and more practically. This study describes the reasons for choosing User-Centred Design or UCD as a methodology to help analysing unstructured users’ requirements. Moreover, it presents surveys as a chosen UCD method to help user to focus more on main requirements and they also increase the speed of gathering information from users. The result shows that survey is a key point for success of this project. Furthermore, this research analyses two available applications in the market with similar functionalities, ArcGIS and QGIS from all aspects of the User-Centred Design perspective. The outcome of this analysis helps extensively in the evaluation of the final version of the GeoImage application. Finally, this study can be complemented in the future by adding more functionalities based on the final GeoImage’s goal. Furthermore, all analysed requirements can be gathered in a web-based application for public audience.
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Morrell, Casey, Amy Poole, Megan A. Quinn, Shimin Zheng, and Andrew Geosciences Joyner. "Tennessee Stroke Registration Report, 2015." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etsu-works/117.
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Background: Stroke is the fifth leading cause of death in Tennessee. The Tennessee Stroke Registry (TSR) Act requires East Tennessee State University’s College of Public Health to maintain a stroke database of participating hospitals and produce an annual report. Currently, twelve hospitals submit data to the TSR.
Objectives: The TSR seeks to provide stroke information to Tennessee residents, policy makers, and health-care professionals. This presentation will highlight the key findings of the 2015 TSR report and will serve as an update to the 2014 report presented at the 2015 Tennessee Public Health Association conference.
Methods: Data for the TSR was collected via Quintiles, American Heart Association’s online database. Microsoft Excel and ArcMap 10.3.x were used to conduct a descriptive analysis of stroke across Tennessee, observing characteristics of both stroke overall and of individual subtypes.
Results: Seventy-nine percent of strokes in Tennessee in 2015 were ischemic. Some subtypes showed significantly different proportions of males versus females. For instance, females made up 63% of subarachnoid hemorrhage patients. The average age of stroke patients in Tennessee was 67.1 years, but varied for subtypes, ranging from 58.2 to 69 years. The majority of stroke patients (75.1%) had a recorded history of hypertension. Counties with high stroke mortality rates tended to cluster in areas of few certified stroke centers.
Conclusion: Stroke subtypes exhibited different characteristics than stroke overall and geographic disparities were highlighted through the descriptive mapping. Identifying and understanding these differences and disparities can help in addressing ways to improve stroke care in Tennessee.
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Song, Joo Hyun. "Methods for evaluating image registration." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5637.
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In the field of medical imaging, image registration methods are useful for many applications such as inter- and intra-subject morphological comparisons, creation of population atlases, delivery of precision therapies, etc. A user may want to know which is the most suitable registration algorithm that would work best for the intended application, but the vastness of medical image registration applications makes evaluation and comparison of image registration performance a non-trivial task. In general, evaluating image registration performance is not straightforward because in most image registration applications there is an absence of “Gold Standard” or ground truth correspondence map to compare against. It is therefore the primary goal of this thesis work to provide a means for recommending the most appropriate registration algorithm for a given task. One of the contributions of this thesis is to examine image registration algorithm performance at the component level. Another contribution of this thesis is to catalog the benefits and limitations of many of the most commonly used image registration evaluation approaches. One incremental contribution of this thesis was to demonstrate how existing evaluation methods can be applied in the midpoint coordinate system to evaluate some symmetric image registration algorithms such as the SyN registration algorithm. Finally, a major contribution of this thesis was to develop tools to evaluate and visualize 2D and 3D image registration shape collapse. This thesis demonstrates that many current diffeomorphic image registration algorithms suffer from the collapse problem, provides the first visualizations of the collapse problem in 3D for simple shapes and real human brain MR images, and provides the first experiments that demonstrate how adjusting image registration parameters can mitigate the collapse problem to some extent.
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Clark, Adrian James. "OPIRA: The Optical-flow Perspective Invariant Registration Augmentation and other improvements for Natural Feature Registration." Thesis, University of Canterbury. Computer Science and Software Engineering, 2009. http://hdl.handle.net/10092/4071.
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In the domain of computer vision, registration is the process of calculating the transformation between a known object, called a marker, and a camera which is viewing it. Registration is the foundation for a number of applications across a range of disciplines such as augmented reality, medical imaging and robotic navigation.
In the set of two dimensional planar markers, there are two classes: (1) fiducial, which are designed to be easily recognisable by computers but have little to no semantic meaning to people, and (2) natural features, which have meaning to people, but can still be registered by a computer. As computers become more powerful, natural feature markers are increasingly the more popular choice; however there are still a number of inherent problems with this class of markers.
This thesis examines the most common shortcomings of natural feature markers, and proposes and evaluates solutions to these weaknesses. The work starts with a review of the existing planar registration approaches, both fiducial and natural features, with a focus on the strengths and weaknesses of each. From this review, the theory behind planar registration is discussed, from the different coordinate systems and transformations, to the computation of the registration transformation.
With a foundation of planar registration, natural feature registration is decomposed into its main stages, and each stage is described in detail. This leads into a discussion of the complete natural feature registration pipeline, highlighting common issues encountered at each step, and discussing the possible solutions for each issue.
A new implementation of natural feature registration called the Optical-flow Perspective Invariant Registration Augmentation (OPIRA) is proposed, which provides vast improvements in robustness to perspective, rotation and changes in scale to popular registration algorithms such as SIFT, SURF, and the Ferns classifier. OPIRA is shown to improve perspective invariance on average by 15% for SIFT, 25% for SURF and 20% for the Ferns Classifier, as well as provide complete rotation invariance for the rotation dependent implementations of these algorithms.
From the investigation into problems and potential resolutions at each stage during registration, each proposed solution is evaluated empirically against an external ground truth. The results are discussed and a conclusion on the improvements gained by each proposed solution and the feasibility of use in a real natural feature registration application is drawn.
Finally, some applications which use the research contained within this thesis are described, as well as some future directions for the research.
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Puwein, Jens. "Multi-view registration of deformable shapes." Zürich : ETH, Eidgenössische Technische Hochschule Zürich, [Department of Computer Science], Applied Geometry Group, 2008. http://e-collection.ethbib.ethz.ch/show?type=dipl&nr=407.
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Roure, Garcia Ferran. "Tools for 3D point cloud registration." Doctoral thesis, Universitat de Girona, 2017. http://hdl.handle.net/10803/403345.
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In this thesis, we did an in-depth review of the state of the art of 3D registration, evaluating the most popular methods. Given the lack of standardization in the literature, we also proposed a nomenclature and a classification to unify the evaluation systems and to be able to compare the different algorithms under the same criteria.
The major contribution of the thesis is the Registration Toolbox, which consists of software and a database of 3D models. The software presented here consists of a 3D Registration Pipeline written in C ++ that allows researchers to try different methods, as well as add new ones and compare them. In this Pipeline, we not only implemented the most popular methods of literature, but we also added three new methods that contribute to improving the state of the art. On the other hand, the database provides different 3D models to be able to carry out the tests to validate the performances of the methods. Finally, we presented a new hybrid data structure specially focused on the search for neighbors. We tested our proposal together with other data structures and we obtained very satisfactory results, overcoming in many cases the best current alternatives. All tested structures are also available in our Pipeline.
This Toolbox is intended to be a useful tool for the whole community and is available to researchers under a Creative Commons licenseEn aquesta tesi, hem fet una revisió en profunditat de l'estat de l'art del registre 3D, avaluant els mètodes més populars. Donada la falta d'estandardització de la literatura, també hem proposat una nomenclatura i una classificació per tal d'unificar els sistemes d'avaluació i poder comparar els diferents algorismes sota els mateixos criteris. La contribució més gran de la tesi és el Toolbox de Registre, que consisteix en un software i una base de dades de models 3D. El software presentat aquí consisteix en una Pipeline de registre 3D escrit en C++ que permet als investigadors provar diferents mètodes, així com afegir-n'hi de nous i comparar-los. En aquesta Pipeline, no només hem implementat els mètodes més populars de la literatura, sinó que també hem afegit tres mètodes nous que contribueixen a millorar l'estat de l'art de la tecnologia. D'altra banda, la base de dades proporciona una sèrie de models 3D per poder dur a terme les proves necessàries per validar el bon funcionament dels mètodes. Finalment, també hem presentat una nova estructura de dades híbrida especialment enfocada a la cerca de veïns. Hem testejat la nostra proposta conjuntament amb altres estructures de dades i hem obtingut resultats molt satisfactoris, superant en molts casos les millors alternatives actuals. Totes les estructures testejades estan també disponibles al nostre Pipeline. Aquesta Toolbox està pensada per ésser una eina útil per tota la comunitat i està a disposició dels investigadors sota llicència Creative-Commons
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Yeung, Sai Kit. "Stochastic framework for inverse consistent registration /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?BIEN%202005%20YEUNG.
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Chou, Yi-Yu. "Transitive and Symmetric Nonrigid Image Registration." Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4966.
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The main topic of this thesis is nonrigid image registration for medical applications. We start with an overview and classification of existing registration techniques. We develop a general nonrigid image registration algorithm. It uses spline functions to describe the deformation and uses multi-scale strategy to search for the
optimal transformation. Then we present a new registration operator that is transitive and symmetric. We investigate the theoretical implication of these properties and apply this
operator to the registration of sequences of MR cardiac images.
In the second part of the thesis, two methods, one 2D and one 3D, for validation of nonrigid image registration algorithms are proposed and compared to a manual validation strategy. Both
methods provide pairs of deformed images as well as corresponding true displacement fields with known accuracy. Nonrigid registration algorithms can be run on the pairs of images and their outputs can be compared to the true displacement fields that were generated manually by five observers. While these phantom validation studies do not provide physically correct deformations,
they are certainly a useful way to test the algorithm's ability to recover various deformation patterns.
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Li, Shuo. "Registration of 3D Volumetric CT Images." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-162599.
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This master thesis aims to develop a system for analyzing transformation between two volumetric CT images. The volumetric image data we process is taken from a composite material. This composite material combines wood fibre and plastic and can be used to make for instance hockey sticks or furniture. Because of the wood fibre embedded in this composite material, it absorbs water and sometimes deforms. By observing volumetric images generated by micro computed tomography (micro-CT), we know that the organization of fibre embedded in this material is very complicated. This makes it difficult to predict the deformation on beforehand. In our study, we have seen rigid transformations, non-rigid transformations and even discontinuities transformations (cracks). For a pair of very small sub volumes, in dry and wet condition, we have found that the transformation can approximated by a rigid transformation combined with a scaling value. To find this transformation, our system includes two key phases. In the first phase, we extract feature points in dry and wet condition. In the second phase, we register the feature points derived from dry and wet condition. In the feature point extraction phase, we have adapted different methods, for instance the Scale- Invariant Feature Transform (SIFT) method is used to extract features. In the registration phase, we have tested three different registration algorithms. The first algorithm is based on concepts from Random Sample Consensus (RANSAC). The second algorithm is inspired from the Iterative Closest Point (ICP) method. The third method is a novel algorithm that we call Spatial Invariant Registration. In the report, we compare the different methods in the feature extraction phase and in the registration phase. Finally, we discuss how our system can be extended to give better results with better accuracy.
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Ye, Getian Information Technology & Electrical Engineering Australian Defence Force Academy UNSW. "Image registration and super-resolution mosaicing." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Information Technology and Electrical Engineering, 2005. http://handle.unsw.edu.au/1959.4/38653.
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This thesis presents new approaches to image registration and super-resolution mosaicing as well as their applications. Firstly, a feature-based image registration method is proposed for a multisensor surveillance system that consists of an optical camera and an infrared camera. By integrating a non-rigid object tracking technique into this method, a novel approach to simultaneous object tracking and multisensor image registration is proposed. Based on the registration and fusion of multisensor information, automatic face detection is greatly improved. Secondly, some extensions of a gradient-based image registration method, called inverse compositional algorithm, are proposed. These extensions include cumulative multi-image registration and the incorporation of illumination change and lens distortion correction. They are incorporated into the framework of the original algorithm in a consistent manner and efficiency can still be achieved for multi-image registration with illumination and lens distortion correction. Thirdly, new super-resolution mosaicing algorithms are proposed for multiple uncompressed and compressed images. Considering the process of image formation, observation models are introduced to describe the relationship between the superresolution mosaic image and the uncompressed and compressed low-resolution images. To improve the performance of super-resolution mosaicing, a wavelet-based image interpolation technique and an approach to adaptive determination of the regularization parameter are presented. For compressed images, a spatial-domain algorithm and a transform-domain algorithm are proposed. All the proposed superresolution mosaicing algorithms are robust against outliers. They can produce superresolution mosaics and reconstructed super-resolution images with improved subjective quality. Finally, new techniques for super-resolution sprite generation and super-resolution sprite coding are proposed. Considering both short-term and long-term motion influences, an object-based image registration method is proposed for handling long image sequences. In order to remove the influence of outliers, a robust technique for super-resolution sprite generation is presented. This technique produces sprite images and reconstructed super-resolution images with high visual quality. Moreover, it provides better reconstructed low-resolution images compared with low-resolution sprite generation techniques. Due to the advantages of the super-resolution sprite, a super-resolution sprite coding technique is also proposed. It achieves high coding efficiency especially at a low bit-rate and produces both decoded low-resolution and super-resolution images with improved subjective quality. Throughout this work, the performance of all the proposed algorithms is evaluated using both synthetic and real image sequences.
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Safari-Foroushani, Ramin. "Form registration, a computer vision approach." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0012/NQ52413.pdf.
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Liu, Yuping. "Land registration, China's experience and prospects." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ63327.pdf.
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Sotiras, Aristeidis. "Discrete Image Registration : a Hybrid Paradigm." Phd thesis, Ecole Centrale Paris, 2011. http://tel.archives-ouvertes.fr/tel-00677442.
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This thesis is devoted to dense deformable image registration/fusion using discrete methods. The main contribution of the thesis is a principled registration framework coupling iconic/geometric information through graph-based techniques. Such a formulation is derived from a pair-wise MRF view-point and solves both problems simultaneously while imposing consistency on their respective solutions. The proposed framework was used to cope with pair-wise image fusion (symmetric and asymmetric variants are proposed) as well as group-wise registration for population modeling. The main qualities of our framework lie in its computational efficiency and versatility. The discrete nature of the formulation renders the framework modular in terms of iconic similarity measures as well as landmark extraction and association techniques. Promising results using a standard benchmark database in optical flow estimation and 3D medical data demonstrate the potentials of our methods.
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Reinertsen, Ingerid R. "Robust registration of volumetric image data." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=29570.
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Head motion during fMRI experiments continues to be a significant problem for analysis, producing artifacts that can severely degrade image quality and make interpretation difficult and inaccurate. Such movement artifacts can lead to reduced statistical significance when detecting true activation or may lead to the creation of spurious activations. To address the problem of interscan motion, a retrospective image registration method has been developed. The registration technique is based on the use of non-linear deformation fields, the least-trimmed-squares robust estimator and Procrustes analysis.The registration algorithm was validated using simulated anatomical MRI volumes and real fMRI datasets. The registration technique is robust in the presence of large amounts of noise; and the experiments show that the method gives accurate estimations of motion up to 5 mm translation in all three directions and 5 degrees rotation around the three axes. The correction procedure also yields increased statistical power in activated regions, and thereby facilitates the precise localization of true activated areas.
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Gu, Wei Q. "Automated tracer-independent MRIPET image registration." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=27223.
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Existing MRI/PET registration methods are tracer-dependent and may not work well with the PET emission images obtained using tracers which only accumulate - significantly in specific regions, or with PET images of pathology which have abnormal tracer distribution.This thesis describes an automated tracer-independent MRI/PET registration method, in which the registration of MR images to tracer-independent PET transmission images is performed to register the corresponding MRI and PET emission images. Two voxel-based registration methods--mutual information method (MI) and voxel intensity ratio (VR) method, were implemented for the registration of MRI/PET transmission images.
The validation of the two registration methods was first performed on simulated PET transmission images with real MR images. The quantitative evaluation of these registration results reveals that the MI method gives more accurate registration results (mean 3-D registration error less than 2 mm) than the VR method (mean 3-D registration error more than 2.5 mm); and the MI method is more robust against noise and data truncation than the VR method. Both methods are more sensitive to low spatial resolution than to the noise of the PET transmission images. The validation of the MI method on real MRI/PET images was also carried out, and the results show no obvious misregistration by visual inspection. Tracer-independent MRI/PET registration using the MI algorithm is shown to be a feasible and robust method to register the MRI to PET images, regardless of the tracer used in the PET studies.
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Xu, Dongjiang. "HYBRID AND HIERARCHICAL IMAGE REGISTRATION TECHNIQUES." Doctoral diss., University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3232.
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A large number of image registration techniques have been developed for various types of sensors and applications, with the aim to improve the accuracy, computational complexity, generality, and robustness. They can be broadly classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in scale, rotation, and translation. In addition, intensity-based methods lack the robustness in the presence of non-spatial distortions due to different imaging conditions between images. In this dissertation, the image registration is formulated as a two-stage hybrid approach combining both an initial matching and a final matching in a coarse-to-fine manner. In the proposed hybrid framework, the initial matching algorithm is applied at the coarsest scale of images, where the approximate transformation parameters could be first estimated. Subsequently, the robust gradient-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution scheme. Several novel and effective initial matching algorithms have been proposed for the first stage. The variations of the intensity characteristics between images may be large and non-uniform because of non-spatial distortions. Therefore, in order to effectively incorporate the gradient-based robust estimation into our proposed framework, one of the fundamental questions should be addressed: what is a good image representation to work with using gradient-based robust estimation under non-spatial distortions. With the initial matching algorithms applied at the highest level of decomposition, the proposed hybrid approach exhibits superior range of convergence. The gradient-based algorithms in the second stage yield a robust solution that precisely registers images with sub-pixel accuracy. A hierarchical iterative searching further enhances the convergence range and rate. The simulation results demonstrated that the proposed techniques provide significant benefits to the performance of image registration.Ph.D.
Department of Electrical and Computer Engineering
Engineering and Computer Science
Electrical Engineering
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Bejo, Siti. "Elastic image registration for landslides monitoring." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/804429/.
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Lester, Hava. "Non-linear registration of medical images." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325162.
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Borsub, Jatesada. "Hardened Registration Process for Participatory Sensing." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-247886.
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Participatory sensing systems need to gather information from a largenumber of participants. However, the openness of the system is a doubleedgedsword: by allowing practically any user to join, the system can beabused by an attacker who introduces a large number of virtual devices.This work proposes a hardened registration process for participatory sensingto raise the bar: registrations are screened through a number of defensivemeasures, towards rejecting spurious registrations that do not correspondto actual devices. This deprives an adversary from a relatively easytake-over and, at the same time, allows a flexible and open registrationprocess. The defensive measures are incorporated in the participatorysensing application.Deltagande avkännings system behöver samlas från ett stort antal aktörer.Systems öppenhet är dock en dubbelsidigt värd: Genom att låta alla praktiskaanvändare deltagit, kan system utnyttja en av angripare som introducera ett stortantal virtuella enheter. I det här arbetet föreslå en härda registreringsprocess fördeltagare att identifiera höjning av ribban: registrering screenas genom ett antaldefensiva åtgärders, för att avvisa falska registreringar som inte motsvara aktuellaenheter. Detta berövar en motståndare från en relativt lätt övertagande och gersamtidigt en flexibel och öppen registreringsprocess. De defensiva åtgärdernainförlivas i deltagande avkännings applikation.