Relevant bibliographies by topics / Alignment of images

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Alignment of images'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 February 2022

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Journal articles on the topic "Alignment of images"

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Lamprinou, Nefeli, Nikolaos Nikolikos, and Emmanouil Z. Psarakis. "Groupwise Image Alignment via Self Quotient Images." Sensors 20, no. 8 (April 19, 2020): 2325. http://dx.doi.org/10.3390/s20082325.

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Compared with pairwise registration, the groupwise one is capable of handling a large-scale population of images simultaneously in an unbiased way. In this work we improve upon the state-of-the-art pixel-level, Least-Squares (LS)-based groupwise image registration methods. Specifically, the registration technique is properly adapted by the use of Self Quotient Images (SQI) in order to become capable for solving the groupwise registration of photometrically distorted, partially occluded as well as unimodal and multimodal images. Moreover, the proposed groupwise technique is linear to the cardinality of the image set and thus it can be used for the successful solution of the problem on large image sets with low complexity. From the application of the proposed technique on a series of experiments for the groupwise registration of photometrically and geometrically distorted, partially occluded faces as well as unimodal and multimodal magnetic resonance image sets and its comparison with the Lucas–Kanade Entropy (LKE) algorithm, the obtained results look very promising, in terms of alignment quality, using as figures of merit the mean Peak Signal to Noise Ratio ( m P S N R ) and mean Structural Similarity ( m S S I M ), and computational cost.
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Haselgrove, John, Lou Fodor, and Lee Peachey. "Automatic alignment of stereo images." Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 502–3. http://dx.doi.org/10.1017/s0424820100170244.

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Stereoscopic pairs of electron microscope images are used for quantitative 3D information. A prerequisite for the measurement is to position the two images correctly relative to each other and with the stereo rotation axis of each image aligned vertically for viewing. Although this alignment procedure is relatively straightforward to perform using prints of the images, it is not straightforwardto do once the images have been digitized directly from the microscope. We have developed an algorithm for determining the parameters needed for orienting digitized images. Four parameters are needed: The displacements Δx and Δy by which one of the images must be translated to be superimposed on the other, and the angles Θ1 and Θr by which the left and right images must be rotated to bring the stereo-rotation axis vertical.The microscopist first uses an interactive routine to identify the coordinates xl(i),yl(i) and xr(i),yr(i) of a number (N) of fiducial points which can easily be recognized on each image.
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Mohammad Khidher Mohammed A. M. Al-taee, Israa. "Creating Image Mosaics using Statistical Methods for Images Alignment." JOURNAL OF EDUCATION AND SCIENCE 24, no. 1 (March 1, 2011): 93–107. http://dx.doi.org/10.33899/edusj.2011.51409.

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Wang, C. W., and H. C. Chen. "Improved image alignment method in application to X-ray images and biological images." Bioinformatics 29, no. 15 (May 29, 2013): 1879–87. http://dx.doi.org/10.1093/bioinformatics/btt309.

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Wang, Guan-An, Tianzhu Zhang, Yang Yang, Jian Cheng, Jianlong Chang, Xu Liang, and Zeng-Guang Hou. "Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 12144–51. http://dx.doi.org/10.1609/aaai.v34i07.6894.

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RGB-Infrared (IR) person re-identification is very challenging due to the large cross-modality variations between RGB and IR images. The key solution is to learn aligned features to the bridge RGB and IR modalities. However, due to the lack of correspondence labels between every pair of RGB and IR images, most methods try to alleviate the variations with set-level alignment by reducing the distance between the entire RGB and IR sets. However, this set-level alignment may lead to misalignment of some instances, which limits the performance for RGB-IR Re-ID. Different from existing methods, in this paper, we propose to generate cross-modality paired-images and perform both global set-level and fine-grained instance-level alignments. Our proposed method enjoys several merits. First, our method can perform set-level alignment by disentangling modality-specific and modality-invariant features. Compared with conventional methods, ours can explicitly remove the modality-specific features and the modality variation can be better reduced. Second, given cross-modality unpaired-images of a person, our method can generate cross-modality paired images from exchanged images. With them, we can directly perform instance-level alignment by minimizing distances of every pair of images. Extensive experimental results on two standard benchmarks demonstrate that the proposed model favourably against state-of-the-art methods. Especially, on SYSU-MM01 dataset, our model can achieve a gain of 9.2% and 7.7% in terms of Rank-1 and mAP. Code is available at https://github.com/wangguanan/JSIA-ReID.
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Monro, D. M., and D. M. Simpson. "Alignment blur in coherently averaged images." IEEE Transactions on Signal Processing 44, no. 6 (June 1996): 1596–601. http://dx.doi.org/10.1109/78.506630.

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SAXTON, W. O. "Accurate alignment of sets of images." Journal of Microscopy 174, no. 2 (May 1994): 61–68. http://dx.doi.org/10.1111/j.1365-2818.1994.tb03449.x.

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Radermacher, Michael, and Teresa Ruiz. "On cross-correlations, averages and noise in electron microscopy." Acta Crystallographica Section F Structural Biology Communications 75, no. 1 (January 1, 2019): 12–18. http://dx.doi.org/10.1107/s2053230x18014036.

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Biological samples are radiation-sensitive and require imaging under low-dose conditions to minimize damage. As a result, images contain a high level of noise and exhibit signal-to-noise ratios that are typically significantly smaller than 1. Averaging techniques, either implicit or explicit, are used to overcome the limitations imposed by the high level of noise. Averaging of 2D images showing the same molecule in the same orientation results in highly significant projections. A high-resolution structure can be obtained by combining the information from many single-particle images to determine a 3D structure. Similarly, averaging of multiple copies of macromolecular assembly subvolumes extracted from tomographic reconstructions can lead to a virtually noise-free high-resolution structure. Cross-correlation methods are often used in the alignment and classification steps of averaging processes for both 2D images and 3D volumes. However, the high noise level can bias alignment and certain classification results. While other approaches may be implicitly affected, sensitivity to noise is most apparent in multireference alignments, 3D reference-based projection alignments and projection-based volume alignments. Here, the influence of the image signal-to-noise ratio on the value of the cross-correlation coefficient is analyzed and a method for compensating for this effect is provided.
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Nagumo, Kent, Tomohiro Kobayashi, Kosuke Oiwa, and Akio Nozawa. "Face Alignment in Thermal Infrared Images Using Cascaded Shape Regression." International Journal of Environmental Research and Public Health 18, no. 4 (February 12, 2021): 1776. http://dx.doi.org/10.3390/ijerph18041776.

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The evaluation of physiological and psychological states using thermal infrared images is based on the skin temperature of specific regions of interest, such as the nose, mouth, and cheeks. To extract the skin temperature of the region of interest, face alignment in thermal infrared images is necessary. To date, the Active Appearance Model (AAM) has been used for face alignment in thermal infrared images. However, computation using this method is costly, and it has a low real-time performance. Conversely, face alignment of visible images using Cascaded Shape Regression (CSR) has been reported to have high real-time performance. However, no studies have been reported on face alignment in thermal infrared images using CSR. Therefore, the objective of this study was to verify the speed and robustness of face alignment in thermal infrared images using CSR. The results suggest that face alignment using CSR is more robust and computationally faster than AAM.
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Winz, M. L., K. Rohr, and S. Wörz. "Geometric Alignment of 2D Gel Electrophoresis Images." Methods of Information in Medicine 48, no. 04 (2009): 320–23. http://dx.doi.org/10.3414/me9229.

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Summary Objectives: 2D gel electrophoresis (2-DE) is the method of choice for analyzing protein expression in the field of proteomics, for example, comparing a reference with a test population. However, due to complex physical and chemical processes the locations of proteins generally vary in different 2-DE images. To cope with these variations, accurate geometric alignment of 2-DE images is important. Methods: We introduce a new elastic registration approach for 2-DE images, which is based on an analytic solution of the Navier equation using Gaussian elastic body splines (GEBS). With this approach cross-effects in elastic deformations can be handled, which is important for the registration of 2-DE images. In addition, landmark correspondences can be included to aid the registration in regions which are difficult to register using intensity information alone. Results: We have successfully applied our approach to register 2-DE gel images of different levels of complexity. In each case, gel images from a reference group are compared with a test group. To analyze the performance of our approach, we have carried out a quantitative evaluation of the registration results. Moreover, we have performed an experimental comparison with a previous elastic registration scheme. Conclusions: From the results we found that our approach is well-suited for the registration of 2-DE gel images of different levels of complexity and it turned out that the approach is superior to a previous hybrid scheme. Moreover, our approach is well-suited in a fully automatic setting and the performance can further be improved when landmark correspondences are available.
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Dissertations / Theses on the topic "Alignment of images"

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Gieffers, Amy Christina 1975. "Image alignment algorithms for ultrasound images with contrast." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/46193.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
Includes bibliographical references (leaves 70-74).
by Amy Christina Gieffers.
M.Eng.
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Melbourne, A. "Alignment of contrast enhanced medical images." Thesis, University College London (University of London), 2009. http://discovery.ucl.ac.uk/15846/.

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The re-alignment of series of medical images in which there are multiple contrast variations is difficult. The reason for this is that the popularmeasures of image similarity used to drive the alignment procedure do not separate the influence of intensity variation due to image feature motion and intensity variation due to feature enhancement. In particular, the appearance of new structure poses problems when it has no representation in the original image. The acquisition of many images over time, such as in dynamic contrast enhanced MRI, requires that many images with different contrast be registered to the same coordinate system, compounding the problem. This thesis addresses these issues, beginning by presenting conditions under which conventional registration fails and proposing a solution in the form of a ’progressive principal component registration’. The algorithm uses a statistical analysis of a series of contrast varying images in order to reduce the influence of contrast-enhancement that would otherwise distort the calculation of the image similarity measures used in image registration. The algorithm is shown to be versatile in that it may be applied to series of images in which contrast variation is due to either temporal contrast enhancement changes, as in dynamic contrast-enhanced MRI or intrinsically in the image selection procedure as in diffusion weighted MRI.
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Noble, Nicholas Michael Ian. "Information alignment and extraction from cardiac magnetic resonance images." Thesis, King's College London (University of London), 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.415344.

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Matos, Luís Miguel de Oliveira. "Lossless compression algorithms for microarray images and whole genome alignments." Doctoral thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/14273.

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Doutoramento em Informática
Nowadays, in the 21st century, the never-ending expansion of information is a major global concern. The pace at which storage and communication resources are evolving is not fast enough to compensate this tendency. In order to overcome this issue, sophisticated and efficient compression tools are required. The goal of compression is to represent information with as few bits as possible. There are two kinds of compression, lossy and lossless. In lossless compression, information loss is not tolerated so the decoded information is exactly the same as the encoded one. On the other hand, in lossy compression some loss is acceptable. In this work we focused on lossless methods. The goal of this thesis was to create lossless compression tools that can be used in two types of data. The first type is known in the literature as microarray images. These images have 16 bits per pixel and a high spatial resolution. The other data type is commonly called Whole Genome Alignments (WGA), in particularly applied to MAF files. Regarding the microarray images, we improved existing microarray-specific methods by using some pre-processing techniques (segmentation and bitplane reduction). Moreover, we also developed a compression method based on pixel values estimates and a mixture of finite-context models. Furthermore, an approach based on binary-tree decomposition was also considered. Two compression tools were developed to compress MAF files. The first one based on a mixture of finite-context models and arithmetic coding, where only the DNA bases and alignment gaps were considered. The second tool, designated as MAFCO, is a complete compression tool that can handle all the information that can be found in MAF files. MAFCO relies on several finite-context models and allows parallel compression/decompression of MAF files.
Hoje em dia, no século XXI, a expansão interminável de informação é uma grande preocupação mundial. O ritmo ao qual os recursos de armazenamento e comunicação estão a evoluir não é suficientemente rápido para compensar esta tendência. De forma a ultrapassar esta situação, são necessárias ferramentas de compressão sofisticadas e eficientes. A compressão consiste em representar informação utilizando a menor quantidade de bits possível. Existem dois tipos de compressão, com e sem perdas. Na compressão sem perdas, a perda de informação não é tolerada, por isso a informação descodificada é exatamente a mesma que a informação que foi codificada. Por outro lado, na compressão com perdas alguma perda é aceitável. Neste trabalho, focámo-nos apenas em métodos de compressão sem perdas. O objetivo desta tese consistiu na criação de ferramentas de compressão sem perdas para dois tipos de dados. O primeiro tipo de dados é conhecido na literatura como imagens de microarrays. Estas imagens têm 16 bits por píxel e uma resolução espacial elevada. O outro tipo de dados é geralmente denominado como alinhamento de genomas completos, particularmente aplicado a ficheiros MAF. Relativamente às imagens de microarrays, melhorámos alguns métodos de compressão específicos utilizando algumas técnicas de pré-processamento (segmentação e redução de planos binários). Além disso, desenvolvemos também um método de compressão baseado em estimação dos valores dos pixéis e em misturas de modelos de contexto-finito. Foi também considerada, uma abordagem baseada em decomposição em árvore binária. Foram desenvolvidas duas ferramentas de compressão para ficheiros MAF. A primeira ferramenta, é baseada numa mistura de modelos de contexto-finito e codificação aritmética, onde apenas as bases de ADN e os símbolos de alinhamento foram considerados. A segunda, designada como MAFCO, é uma ferramenta de compressão completa que consegue lidar com todo o tipo de informação que pode ser encontrada nos ficheiros MAF. MAFCO baseia-se em vários modelos de contexto-finito e permite compressão/descompressão paralela de ficheiros MAF.
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Queimadelas, Cátia Cristina Arranca. "Automated segmentation, tracking and evaluation of bacteria in microscopy images." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8435.

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
Most of the investigation in microbiology relies on microscope imaging and needs to be complemented with reliable methods of computer assisted image processing, in order to avoid manual analysis. In this work, a method to assist the study of the in vivo kinetics of protein expression from Escherichia coli cells was developed. Confocal fluorescence microscopy (CFM) and Differential Interference Contrast (DIC) microscopy images were acquired and processed using the developed method. This method comprises two steps: the first one is focused on the cells detection using DIC images. The latter aligns both DIC and CFM images and computes the fluorescence level emitted by each cell. For the first step, the Gradient Path Labelling (GPL) algorithm was used which produces a moderate over-segmented DIC image. The proposed algorithm, based on decision trees generated by the Classification and Regression Trees (CART) algorithm, discards the backgrounds regions and merges the regions belonging to the same cell. To align DIC/fluorescence images an exhaustive search of the relative position and scale parameters that maximizes the fluorescence inside the cells is made. After the cells have been located on the CFM images, the fluorescence emitted by each cell is evaluated. The discard classifier performed with an error rate of 1:81% 0:98% and the merge classifier with 3:25% 1:37%. The segmentation algorithm detected 93:71% 2:06% of the cells in the tested images. The tracking algorithm correctly followed 64:52% 16:02% of cells and the alignment method successfully aligned all the tested images.
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Härd, Victoria. "Automatic Alignment of 2D Cine Morphological Images Using 4D Flow MRI Data." Thesis, Linköpings universitet, Datorseende, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131470.

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Cardiovascular diseases are among the most common causes of death worldwide. One of the recently developed flow analysis technique called 4D flow magnetic resonance imaging (MRI) allows an early detection of such diseases. Due to the limited resolution and contrast between blood pool and myocardium of 4D flow images, cine MR images are often used for cardiac segmentation. The delineated structures are then transferred to the 4D Flow images for cardiovascular flow analysis. Cine MR images are however acquired with multiple breath-holds, which can be challenging for some people, especially, when a cardiovascular disease is present. Consequently, unexpected breathing motion by a patient may lead to misalignments between the acquired cine MR images. The goal of the thesis is to test the feasibility of an automatic image registration method to correct the misalignment caused by respiratory motion in morphological 2D cine MR images by using the 4D Flow MR as the reference image. As a registration method relies on a set of optimal parameters to provide desired results, a comprehensive investigation was performed to find such parameters. Different combinations of registration parameters settings were applied on 20 datasets from both healthy volunteers and patients. The best combinations, selected on the basis of normalized cross-correlation, were evaluated using the clinical gold-standard by employing widely used geometric measures of spatial correspondence. The accuracy of the best parameters from geometric evaluation was finally validated by using simulated misalignments. Using a registration method consisting of only translation improved the results for both datasets from healthy volunteers and patients and the simulated misalignment data. For the datasets from healthy volunteers and patients, the registration improved the results from 0.7074 ± 0.1644 to 0.7551 ± 0.0737 in Dice index and from 1.8818 ± 0.9269 to 1.5953 ± 0.5192 for point-to-curve error. These values are a mean value for all the 20 datasets. The results from geometric evaluation on the data from both healthy volunteers and patients show that the developed correction method is able to improve the alignment of the cine MR images. This allows a reliable segmentation of 4D flow MR images for cardiac flow assessment.
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Bergnéhr, Leo. "Segmentation and Alignment of 3-D Transaxial Myocardial Perfusion Images and Automatic Dopamin Transporter Quantification." Thesis, Linköping University, Department of Biomedical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11716.

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Nukleärmedicinska bilder som exempelvis SPECT (Single Photon Emission Tomogra-phy) är en bildgenererande teknik som ofta används i många applikationer vid mätning av fysiologiska egenskaper i den mänskliga kroppen. En vanlig sorts undersökning som använder sig av SPECT är myokardiell perfusion (blodflöde i hjärtvävnaden), som ofta används för att undersöka t.ex. en möjlig hjärtinfarkt. För att göra det möjligt för läkare att ställa en kvalitativ diagnos baserad på dessa bilder, måste bilderna först segmenteras och roteras av en biomedicinsk analytiker. Detta utförs på grund av att hjärtat hos olika patienter, eller hos patienter vid olika examinationstillfällen, inte är lokaliserat och roterat på samma sätt, vilket är ett väsentligt antagande av läkaren vid granskning

av bilderna. Eftersom olika biomedicinska analytiker med olika mängd erfarenhet och expertis roterar bilderna olika uppkommer variation av de slutgiltiga bilder, vilket ofta kan vara ett problem vid diagnostisering.

En annan sorts nukleärmedicinsk undersökning är vid kvantifiering av dopaminreceptorer i de basala ganglierna i hjärnan. Detta utförs ofta på patienter som visar symptom av Parkinsons sjukdom, eller liknande sjukdomar. För att kunna bestämma graden av sjukdomen används ofta ett utförande för att räkna ut olika kvoter mellan områden runt dopaminreceptorerna. Detta är ett tröttsamt arbete för personen som utför kvantifieringen och trots att de insamlade bilderna är tredimensionella, utförs kvantifieringen allt för ofta endast på en eller flera skivor av bildvolymen. I likhet med myokardiell perfusionsundersökningar är variation mellan kvantifiering utförd av olika personer en möjlig felkälla.

I den här rapporten presenteras en ny metod för att automatiskt segmentera hjärtats vänstra kammare i SPECT-bilder. Segmenteringen är baserad på en intensitetsinvariant lokal-fasbaserad lösning, vilket eliminerar svårigheterna med den i myokardiella perfusionsbilder ofta varierande intensiteten. Dessutom används metoden för att uppskatta vinkeln hos hjärtats vänstra kammare. Efter att metoden sedan smått justerats används den som ett förslag på ett nytt sätt att automatiskt kvantifiera dopaminreceptorer i de basala ganglierna, vid användning av den radioaktiva lösningen DaTSCAN.


Nuclear medical imaging such as SPECT (Single Photon Emission Tomography) is an imaging modality which is readily used in many applications for measuring physiological properties of the human body. One very common type of examination using SPECT is when measuring myocardial perfusion (blood flow in the heart tissue), which is often used to examine e.g. a possible myocardial infarction (heart attack). In order for doctors to give a qualitative diagnose based on these images, the images must first be segmented and rotated by a medical technologist. This is performed due to the fact that the heart of different patients, or for patients at different times of examination, is not situated and rotated equally, which is an essential assumption for the doctor when examining the images. Consequently, as different technologists with different amount of experience and expertise will rotate images differently, variability between operators arises and can often become a problem in the process of diagnosing.

Another type of nuclear medical examination is when quantifying dopamine transporters in the basal ganglia in the brain. This is commonly done for patients showing symptoms of Parkinson’s disease or similar diseases. In order to specify the severity of the disease, a scheme for calculating different fractions between parts of the dopamine transporter area is often used. This is tedious work for the person performing the quantification, and despite the acquired three dimensional images, quantification is too often performed on one or more slices of the image volume. In resemblance with myocardial perfusion examinations, variability between different operators can also here present a possible source of errors.

In this thesis, a novel method for automatically segmenting the left ventricle of the heart in SPECT-images is presented. The segmentation is based on an intensity-invariant local-phase based approach, thus removing the difficulty of the commonly varying intensity in myocardial perfusion images. Additionally, the method is used to estimate the angle of the left ventricle of the heart. Furthermore, the method is slightly adjusted, and a new approach on automatically quantifying dopamine transporters in the basal ganglia using the DaTSCAN radiotracer is proposed.

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Kesler, Joseph Michael. "Automated Alignment of Aircraft Wing Radiography Images Using a Modified Rotation, Scale, and Translation Invariant Phase Correlation Algorithm Employing Local Entropy for Peak Detection." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1218604857.

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Petrovic, Aleksandar. "Connectivity driven registration of magnetic resonance images of the human brain." Thesis, University of Oxford, 2010. http://ora.ox.ac.uk/objects/uuid:fd95c6d4-06d2-41b4-b6f2-5cbd73cb83a9.

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Image registration methods underpin many analysis techniques in neuroimaging. They are essential in group studies when images of different individuals or different modalities need to be brought into a common reference frame. This thesis explores the potential of brain connectivity- driven alignment and develops surface registration techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function and structure of the human brain. The first part of this work develops a novel surface registration framework, based on free mesh deformations, which aligns cortical and subcortical surfaces by matching structural connectivity patterns derived using probabilistic tractography (diffusion-weighted MRI). Structural, i.e. white matter, connectivity is a good predictor of functional specialisation and structural connectivity-driven registration can therefore be expected to enhance the alignment of functionally homologous areas across subjects. The second part validates developed methods for cortical surfaces. Resting State Networks are used in an innovative way to delineate several functionally distinct regions, which were then used to quantify connectivity-driven registration performance by measuring the inter- subject overlap before and after registration. Consequently, the proposed method is assessed using an independent imaging modality and the results are compared to results from state-of-the-art cortical geometry-driven surface registration methods. A connectivity-driven registration pipeline is also developed for, and applied to, the surfaces of subcortical structures such as the thalamus. It is carefully validated on a set of artificial test examples and compared to another novel surface registration paradigm based on spherical wavelets. The proposed registration pipeline is then used to explore the differences in the alignment of two groups of subjects, healthy controls and Alzheimer's disease patients, to a common template. Finally, we propose how functional connectivity can be used instead of structural connectivity for driving registrations, as well as how the surface-based framework can be extended to a volumetric one. Apart from providing the benefits such as the improved functional alignment, we hope that the research conducted in this thesis will also represent the basis for the development of templates of structural and functional brain connectivity.
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Ramírez, Orozco Raissel. "High dynamic range content acquisition from multiple exposures." Doctoral thesis, Universitat de Girona, 2016. http://hdl.handle.net/10803/371162.

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The limited dynamic range of digital images can be extended by composing different exposures of the same scene to produce HDR images. This thesis is composed of an overview of the state of the art techniques and three methods to tackle the image alignment and deghosting problems in the HDR imaging domain. The first method detects the areas affected by motion, registers the dynamic objects over a reference image, and combines low-dynamic range values to recover HDR values in the whole image. The second approach builds multiscopic HDR images from LDR multi-exposure images. It is based on a patch match algorithm which was adapted and improved to take advantage of epipolar geometry constraints of stereo images. The last method proposes to replace under/over exposed pixels in the reference image by using valid HDR values from other images in the multi-exposure LDR image sequence.
El limitado rango dinámico de las imágenes digitales puede ampliarse mezclando varias imágenes adquiridas con diferentes valores de exposición. Esta tesis incluye un detallado resumen del estado del arte y tres métodos diferentes para alinear las imágenes y corregir el efecto ’ghosting’ en imágenes HDR. El primer método está centrado en detectar las áreas afectadas por el movimiento y registrar los objetos dinámicos sobre una imagen de referencia de modo que se logre recuperar información a lo largo de toda la imagen. Nuestra segunda propuesta es un método para obtener imágenes HDR multiscópicas a partir de diferentes exposiciones LDR. Está basado en un algoritmo de ’patch match’ que ha sido adaptado para aprovechar las ventajas de las restricciones de la geometría epipolar de imágenes estéreo. Por último proponemos reemplazar los píxeles saturados en la imagen de referencia usando valores correctos de otras imágenes de la secuencia.
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Books on the topic "Alignment of images"

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Franklin, Eric N. Dynamic alignment through imagery. 2nd ed. Champaign, IL: Human Kinetics, 2012.

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Dynamic alignment through imagery. Champaign, Ill: Human Kinetics, 1996.

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Szeliski, Richard. Image alignment and stitching: A tutorial. Boston: Now, 2006.

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Verghese, Gilbert. Perspective alignment back-projection for real-time monocular three-dimensional model-based computer vision. Toronto: Dept. of Computer Science, University of Toronto, 1995.

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Szeliski, Richard. IMAGE ALIGNMENT AND STITCHING. Now Publishers Inc, 2006.

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Franklin, Eric. Dynamic Alignment Through Imagery. Human Kinetics, 2018.

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Dynamic alignment through imagery - 2. edicion. Human Kinetics, 2012.

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Jacquet, Wolfgang. Focus Mutual Information for Medical Image Alignment in Dentistry, Orthodontics and Craniofacial Surgery. Academic & Scientific Publishers, 2010.

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Verghese, Gilbert. Perspective alignment back-projection for real-time monocular three-dimensional model-based computer vision. 1995.

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Gillam, Barbara. Subjective Contours. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0098.

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Subjective contours are perceived edges of surfaces in locations where there is no physical contour in the image. They cannot be regarded as a general neural filling-in process because they only occur as the edges of apparently occluding surfaces (surfaces in a scene that hide other surfaces or contours). This chapter shows how subjective contours are elicited by contextual evidence for surface stratification especially by “inducers” that signal in various ways that they are occluded in the location where the subjective contour appears. This can be two-dimensional information about figure shapes and alignments or three-dimensional information about depth relationships.
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Book chapters on the topic "Alignment of images"

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Luo, Bin, and Edwin R. Hancock. "Procrustes Alignment with the EM Algorithm." In Computer Analysis of Images and Patterns, 623–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48375-6_74.

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Huang, Y., U. Knorr, H. Steinmetz, and R. J. Seitz. "Accurate Alignment and Reslicing of PET Images." In Computer Assisted Radiology / Computergestützte Radiologie, 788. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-49351-5_163.

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Wachinger, Christian, and Nassir Navab. "Alignment of Viewing-Angle Dependent Ultrasound Images." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, 779–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04268-3_96.

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Mohamed, Waleed, A. Ben Hamza, and Khaled Gharaibeh. "Graph-Theoretic Image Alignment Using Topological Features." In Computational Modeling of Objects Represented in Images, 199–209. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12712-0_18.

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Oishi, Takeshi, Atsushi Nakazawa, Ryo Kurazume, and Katsushi Ikeuchi. "A Fast Simultaneous Alignment of Multiple Range Images." In Digitally Archiving Cultural Objects, 89–107. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-75807_6.

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Perperidis, Dimitrios, Anil Rao, Maria Lorenzo-Valdés, Raad Mohiaddin, and Daniel Rueckert. "Spatio-temporal Alignment of 4D Cardiac MR Images." In Functional Imaging and Modeling of the Heart, 205–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44883-7_21.

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Toews, Matthew, Lilla Zöllei, and William M. Wells. "Feature-Based Alignment of Volumetric Multi-modal Images." In Lecture Notes in Computer Science, 25–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38868-2_3.

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Gabrani, Maria, and Oleh J. Tretiak. "Cross individual model-based alignment of volumetric images." In Noblesse Workshop on Non-Linear Model Based Image Analysis, 3–8. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1597-7_1.

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Oishi, Takeshi, Atsushi Nakazawa, Ryo Kurazume, Katsushi Ikeuchi, and Ryusuke Sagawa. "Parallel Alignment of a Large Number of Range Images." In Digitally Archiving Cultural Objects, 109–26. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-75807_7.

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Overgaard, Niels Chr, and Jan Erik Solem. "An Analysis of Variational Alignment of Curves in Images." In Lecture Notes in Computer Science, 480–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11408031_41.

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Conference papers on the topic "Alignment of images"

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Li, Ang, Jianzhong Qi, Rui Zhang, Xingjun Ma, and Kotagiri Ramamohanarao. "Generative Image Inpainting with Submanifold Alignment." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/114.

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Image inpainting aims at restoring missing regions of corrupted images, which has many applications such as image restoration and object removal. However, current GAN-based generative inpainting models do not explicitly exploit the structural or textural consistency between restored contents and their surrounding contexts. To address this limitation, we propose to enforce the alignment (or closeness) between the local data submanifolds (subspaces) around restored images and those around the original (uncorrupted) images during the learning process of GAN-based inpainting models. We exploit Local Intrinsic Dimensionality (LID) to measure, in deep feature space, the alignment between data submanifolds learned by a GAN model and those of the original data, from a perspective of both images (denoted as iLID) and local patches (denoted as pLID) of images. We then apply iLID and pLID as regularizations for GAN-based inpainting models to encourage two different levels of submanifold alignments: 1) an image-level alignment to improve structural consistency, and 2) a patch-level alignment to improve textural details. Experimental results on four benchmark datasets show that our proposed model can generate more accurate results than state-of-the-art models.
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Cheng, Li-Chang, and Joerg Meyer. "Volumetric Image Alignment Utilizing Particle Swarm Optimization." In ASME 2009 4th Frontiers in Biomedical Devices Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/biomed2009-83084.

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In some cases an object can not be completely imaged with a single image. These cases call for taking multiple images and stitching the images together to form a complete view of the object. The images that are dealt with are taken with a confocal laser-scanning microscope. This produces a stack of two-dimensional images that represent the volume in the microscope’s field of view. While the microscope automatically creates a z stack, the positioning of the tiles in x and y is done manually. Therefore, the slices within each stack are assumed to be already aligned. Our technique will take multiple stacks of images and stitch them together to form a single volume. We will use a particle swarm optimization technique to calculate the proper transformations required to produce the final volume.
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Mustra, Mario, Mislav Grgic, and Branka Zovko-Cihlar. "Alignment of X-ray bone images." In 2014 X International Symposium on Telecommunications (BIHTEL). IEEE, 2014. http://dx.doi.org/10.1109/bihtel.2014.6987650.

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Pires, B. E., and P. M. Q. Aguiar. "Featureless global alignment of multiple images." In 2005 International Conference on Image Processing. IEEE, 2005. http://dx.doi.org/10.1109/icip.2005.1529686.

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Huang, Gary B., Vidit Jain, and Erik Learned-Miller. "Unsupervised Joint Alignment of Complex Images." In 2007 IEEE 11th International Conference on Computer Vision. IEEE, 2007. http://dx.doi.org/10.1109/iccv.2007.4408858.

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Gonzalez, Diego Marcos, Gustau Camps-Valls, and Devis Tuia. "Weakly supervised alignment of multisensor images." In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7326341.

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Xi Yin, Xiaoming Liu, Jin Chen, and David M. Kramer. "Multi-leaf alignment from fluorescence plant images." In 2014 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2014. http://dx.doi.org/10.1109/wacv.2014.6836067.

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Bose, A., S. K. Shah, G. P. Reece, M. A. Crosby, E. K. Beahm, M. C. Fingeret, M. K. Markey, and F. A. Merchant. "Automated spatial alignment of 3D torso images." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6092086.

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Poleg, Yair, and Shmuel Peleg. "Alignment and mosaicing of non-overlapping images." In 2012 IEEE International Conference on Computational Photography (ICCP). IEEE, 2012. http://dx.doi.org/10.1109/iccphot.2012.6215214.

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Homola, Tomas, Vlastislav Dohnal, and Pavel Zezula. "Searching for Sub-images Using Sequence Alignment." In 2011 IEEE International Symposium on Multimedia (ISM). IEEE, 2011. http://dx.doi.org/10.1109/ism.2011.19.

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Reports on the topic "Alignment of images"

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Shields, Janet E., Richard W. Johnson, Monette E. Karr, Richard A. Weymouth, and David S. Sauer. Delivery and Development of a Day/Night Whole Sky Imager with Enhanced Angular Alignment for Full 24 Hour Cloud Distribution Assessment. Fort Belvoir, VA: Defense Technical Information Center, March 1997. http://dx.doi.org/10.21236/ada333269.

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