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Tesi sul tema "Image registration"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 25 luglio 2025

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1

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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Suri, Sahil. "Automatic image to image registration for multimodal remote sensing images." kostenfrei, 2010. https://mediatum2.ub.tum.de/node?id=967187.

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3

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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4

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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5

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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6

Rohrer, Jonathan. "Accelerated nonrigid image registration." Berlin dissertation.de, 2009. http://d-nb.info/999883968/04.

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7

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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Abstract (sommario):
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 RayStat
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8

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 p
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9

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 it
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10

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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11

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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12

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
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13

Song, Joo Hyun. "Methods for evaluating image registration." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5637.

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Abstract (sommario):
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 registr
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14

Cabrera, Gil Blanca. "Deep Learning Based Deformable Image Registration of Pelvic Images." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279155.

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Deformable image registration is usually performed manually by clinicians,which is time-consuming and costly, or using optimization-based algorithms, which are not always optimal for registering images of different modalities. In this work, a deep learning-based method for MR-CT deformable image registration is presented. In the first place, a neural network is optimized to register CT pelvic image pairs. Later, the model is trained on MR-CT image pairs to register CT images to match its MR counterpart. To solve the unavailability of ground truth data problem, two approaches were used. For the
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15

Zhao, Bowen. "Tissue preserving deformable image registration for 4DCT pulmonary images." Thesis, University of Iowa, 2016. https://ir.uiowa.edu/etd/2172.

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This thesis mainly focuses on proposing a 4D (three spatial dimensions plus time) tissue-volume preserving non-rigid image registration algorithm for pulmonary 4D computed tomography (4DCT) data sets to provide relevant information for radiation therapy and to estimate pulmonary ventilation. The sum of squared tissue volume difference (SSTVD) similarity cost takes into account the CT intensity changes of spatially corresponding voxels, which is caused by variations of the fraction of tissue within voxels throughout the res
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16

Hamdan, Iyas. "Multimodal Image Registration in Image-Guided Prostate Brachytherapy." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0002/document.

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Le cancer de la prostate est le cancer le plus fréquent chez l'homme en France et aux pays occidentaux. Il est la troisième cause de décès liés au cancer, étant responsable d'environ 10% des morts. La curiethérapie, une technique de radiothérapie, est liée à une meilleure qualité de vie après le traitement, par rapport aux autres méthodes de traitement. La curiethérapie de la prostate consiste à insérer des sources radioactives dans la prostate afin de délivrer une dose d'irradiation localisée à la tumeur tout en protégeant les tissus sains environnants. L'imagerie multimodale est utilisée afi
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17

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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Abstract (sommario):
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
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18

Xu, Min. "Image registration and image fusion Algorithms and performance bounds /." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2009. http://wwwlib.umi.com/cr/syr/main.

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19

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
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20

Ye, Getian Information Technology &amp 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-
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21

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
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22

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 anal
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23

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.<br>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 rat
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24

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
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25

Bejo, Siti. "Elastic image registration for landslides monitoring." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/804429/.

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26

Ettinger, Gil J. "Hierarchical three-dimensional medical image registration." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10448.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.<br>Includes bibliographical references (leaves 168-172).<br>by Gil J. Ettinger.<br>Ph.D.
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27

Zeledon, Lostalo Emilia Maria. "FMRI IMAGE REGISTRATION USING DEEP LEARNING." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/theses/2641.

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fMRI imaging is considered key on the understanding of the brain and the mind, for this reason has been the subject of tremendous research connecting different disciplines. The intrinsic complexity of this 4-D type of data processing and analysis has been approached with every single computational perspective, lately increasing the trend to include artificial intelligence. One step critical on the fMRI pipeline is image registration. A model of Deep Networks based on Fully Convolutional Neural Networks, spatial transformation neural networks with a self-learning strategy was proposed for the i
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28

Khare, Vinod. "Precise Image Registration and Occlusion Detection." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1308246730.

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29

Gong, Lixin. "Prostate ultrasound image segmentation and registration /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/5937.

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30

Castro, Pareja Carlos Raul. "Real-time 3D elastic image registration." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1086185793.

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Thesis (Ph. D.)--Ohio State University, 2004.<br>Title from first page of PDF file. Document formatted into pages; contains xv, 105 p. : ill. (some col.). Advisor: Jogikal Jagadeesh, Department of Electrical and Computer Engineering. Includes bibliographical references (p. 101-105).
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31

Zheng, Chaojie. "Deformable Image Registration with Uncertainty-Awareness." Thesis, The University of Sydney, 2019. http://hdl.handle.net/2123/20948.

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Abstract (sommario):
The popularization of information-sensing devices and rapid development of data storage and computing capability have launched the ongoing data explosion, and the value of such information assets has been widely acknowledged. Data often come in high volume, variety and velocity, and people are striving to mine useful information and new knowledge from the growing data sets for various domain applications. The fusion of heterogeneous types of data becomes increasingly essential for analysis and decision making in data incentive industry, especially in healthcare industry. Image registration, as
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32

Kochan, Martin. "Enhancing registration for image-guided neurosurgery." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10045247/.

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Pharmacologically refractive temporal lobe epilepsy and malignant glioma brain tumours are examples of pathologies that are clinically managed through neurosurgical intervention. The aims of neurosurgery are, where possible, to perform a resection of the surgical target while minimising morbidity to critical structures in the vicinity of the resected brain area. Image-guidance technology aims to assist this task by displaying a model of brain anatomy to the surgical team, which may include an overlay of surgical planning information derived from preoperative scanning such as the segmented rese
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33

Björck, Olof. "Analyzing gyro data based image registration." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-397459.

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An analysis of gyro sensor data with regards to rotational image registration is conducted in this thesis. This is relevant for understanding how well images captured with a moving camera can be registered using only gyro sensor data as motion input. This is commonly the case for Electronic Image Stabilization (EIS) in handheld devices. The theory explaining how to register images based on gyro sensor data is presented, a qualitative analysis of gyro sensor data from three generic Android smartphones is conducted, and rotational image registration simulations using simulated noise as well as r
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34

Jia, Zhen. "Image Registration and Image Completion: Similarity and Estimation Error Optimization." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406821875.

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35

Mitra, Jhimli. "Multimodal Image Registration applied to Magnetic Resonance and Ultrasound Prostatic Images." Phd thesis, Université de Bourgogne, 2012. http://tel.archives-ouvertes.fr/tel-00786032.

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This thesis investigates the employment of different deformable registration techniques to register pre-operative magnetic resonance and inter-operative ultrasound images during prostate biopsy. Accurate registration ensures appropriate biopsy sampling of malignant prostate tissues and reduces the rate of re-biopsies. Therefore, we provide comparisons and experimental results for some landmark- and intensity-based registration methods: thin-plate splines, free-form deformation with B-splines. The primary contribution of this thesis is a new spline-based diffeomorphic registration framework for
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36

Yu, Hongliang. "Automatic Rigid and Deformable Medical Image Registration." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050905-100341/.

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37

Chen, Hua-Mei. "Mutual information-based image registration with applications." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2002. http://wwwlib.umi.com/cr/syr/main.

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38

Yi, Zhao. "Nonrigid Image Registration Using Physically Based Models." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2952.

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It is well known that biological structures such as human brains, although may contain the same global structures, differ in shape, orientation, and fine structures across individuals and at different times. Such variabilities during registration are usually represented by nonrigid transformations. This research seeks to address this issue by developing physically based models in which transformations are constructed to obey certain physical laws. <br /><br /> In this thesis, a novel registration technique is presented based on the physical behavior of particles. Regarding the image
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39

Sivaramakrishna, Radhika. "Breast image registration using a textural transformation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23666.pdf.

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40

Gu, Wei Q. "Automated tracer-independent MRI/PET image registration." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29596.pdf.

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41

Lorenzen, Peter Jonathan Joshi Sarang C. "Multi-modal image registration and atlas formation." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2006. http://dc.lib.unc.edu/u?/etd,336.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2006.<br>Title from electronic title page (viewed Oct. 10, 2007). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science." Discipline: Computer Science; Department/School: Computer Science.
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42

Curran, Kathleen Mary. "Orientation matching for diffusion tensor image registration." Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1444595/.

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This thesis develops a registration algorithm specifically for diffusion-tensor (DT) images. The proposed approach matches the tensor orientations to find the registration transformation. Early results show that local optimisation does not find the global minimum in registration of DT-MR brain images. Therefore, a global optimisation registration technique is also implemented. This thesis proposes several new similarity measures for DT registration and provides a comparison of them along with several others previously proposed in the literature. The thesis also proposes several new performance
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43

Cahill, Nathan D. "Constructing and solving variational image registration problems." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:ed43a6f4-216f-45b5-88c5-2baaba1e684a.

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Abstract (sommario):
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
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44

White, Brandyn A. "Using FPGAs to perform embedded image registration." Honors in the Major Thesis, University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1337.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.<br>Bachelors<br>Engineering and Computer Science<br>Computer Engineering
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45

Martin, Stefan. "On information measures for medical image registration." Thesis, University of Strathclyde, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436843.

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46

Williams, Tamara S. (Tamara Shanese) 1976. "Multi-modal registration for image-guided therapy." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86626.

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47

Cuesta, Contreras Angel. "Geometric and photometric affine invariant image registration." Thesis, Heriot-Watt University, 2009. http://hdl.handle.net/10399/2228.

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This thesis aims to present a solution to the correspondence problem for the registration of wide-baseline images taken from uncalibrated cameras. We propose an affine invariant descriptor that combines the geometry and photometry of the scene to find correspondences between both views. The geometric affine invariant component of the descriptor is based on the affine arc-length metric, whereas the photometry is analysed by invariant colour moments. A graph structure represents the spatial distribution of the primitive features; i.e. nodes correspond to detected high-curvature points, whereas a
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48

Dorgham, Osama. "High speed 2D/3D medical image registration." Thesis, University of East Anglia, 2010. https://ueaeprints.uea.ac.uk/32227/.

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49

Ivarsson, Magnus. "Evaluation of 3D MRI Image Registration Methods." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139075.

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Abstract (sommario):
Image registration is the process of geometrically deforming a template image into a reference image. This technique is important and widely used within thefield of medical IT. The purpose could be to detect image variations, pathologicaldevelopment or in the company AMRA’s case, to quantify fat tissue in variousparts of the human body.From an MRI (Magnetic Resonance Imaging) scan, a water and fat tissue image isobtained. Currently, AMRA is using the Morphon algorithm to register and segment the water image in order to quantify fat and muscle tissue. During the firstpart of this master thesis,
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50

Geng, Xiujuan. "Transitive inverse-consistent image registration and evaluation." Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/131.

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