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检索条件"任意字段=Conference on Image Reconstruction from Incomplete Data III"

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MR image reconstruction from data Acquired on an Irregular K-space trajectory 36

MR Image Reconstruction from Data Acquired on an Irregular <...

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36th IEEE International conference on Electronics and Nanotechnology (ELNANO)

作者： Gavrilyuk, V. S. Netreba, A., V Radchenko, S. P. Taras Shevchenko Natl Univ Kyiv Fac Radiophys Elect & Comp Syst Kiev Ukraine

ISBN: (纸本)9781509014316

The reconstruction for the magnetic resonance imaging under condition of using irregular measured signal data array for reconstructing of the spine density spatial distribution are offered. For experimentally measured data using a Fourier-Zymography in Magnetic Resonance Imaging techniques simulated the received signal and realised the reverse reconstruction of tomograms. The evaluation of the quality of tomograms with incomplete signal data set has been carried out.

关键词： Magnetic resonance imaging reconstruction K-space incomplete data

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In Defense of Shallow Learned Spectral reconstruction from RGB images

In Defense of Shallow Learned Spectral Reconstruction from R...

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International conference on Computer Vision Workshops (ICCV Workshops)

作者： Jiqing Wu Jonas Aeschbacher Radu Timofte D-ITET ETH Computer Vision Lab Zurich

Very recent Galliani et al. [13] proposed a method using a very deep CNN architecture for learned spectral reconstruction and showed large improvements over the recent sparse coding method of Arad et al. [6]. In this paper we defend the shallow learned spectral reconstruction methods by: (i) first, reimplementing Arad and showing that it can achieve significantly better results than those originally reported; (ii) second, introducing a novel shallow method based on A+ of Timofte et al. [33] from super-resolution that substantially improves over Arad and, moreover, provides comparable performance to Galliani's very deep CNN method on three standard benchmarks (ICVL, CAVE, and NUS); and (iii) finally, arguing that the train and runtime efficiency as well as the clear relation between its parameters and the achieved performance makes from our shallow A+ a strong baseline for further research in learned spectral reconstruction from RGB images. Moreover, our shallow A+ (as well as Arad) requires and uses significantly smaller train data than Galliani (and generally the CNN approaches), is robust to overfitting and is easily deployable by fast training to newer cameras.

关键词： Hyperspectral imaging Dictionaries image reconstruction Training Spatial resolution

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Multi-modal weighted quadratic priors for robust intensity independent synergistic PET-MR reconstruction

Multi-modal weighted quadratic priors for robust intensity i...

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IEEE Nuclear Science Symposium

作者： Abolfazl Mehranian Martin A. Belzunce Colm J. McGinnity Claudia Prieto Alexander Hammers Andrew J. Reader School of Biomedical Engineering and Imaging Sciences King's College London Department of Biomedical Engineering School of Biomedical Engineering and Imaging Sciences King's College London

ISBN: (纸本)9781538622834

In this work, a robust methodology is presented for synergistic PET-MR image reconstruction, irrespective of their relative signal intensities and contrasts. Mutually-weighted quadratic priors were devised to encourage the formation of common boundaries between PET and MR images while reducing noise, PET Gibbs and MR under-sampling artefacts. These priors are iteratively reweighted using normalized multi-modal Gaussian similarity kernels to modulate smoothing across common boundaries. Synergistic reconstruction was performed using a 3-step optimization: i) maximum a posteriori expectation maximization (MAP-EM) for regularized PET reconstruction, ii) penalized weighted least squares with the conjugate gradient algorithm (PWLS-CG) for regularized sensitivity encoding (SENSE) parallel MR reconstruction and iii) update of joint Gaussian kernels. The performance of the proposed prior was compared against standard reconstruction, separate total variation (TV) regularization and prior-image guided reconstruction using 3D realistic simulations and a real PET-MR dataset. Our results showed that TV regularization reduces noise and artifacts in PET and MR images, but at the expense of resolution degradation, while prior-image guided reconstructions, which exploit high quality fully-sampled MR data, notably improve the image quality but at the expense of suppressing unique lesions. Whereas the proposed method, which exploits information obtained from PET and undersampled MR images, leads to noise and artefact reduction while recovery the details and preserving unique lesions. In conclusion, the proposed algorithm was found promising for multi-modal synergistic image reconstruction.

关键词： PET Scan Polyethylene Terephthalates Reconstructive Surgical Procedures common boundary image reconstruction Signal Intensity Noise reconstructions Artifacts image quality Quadratic smoothing Least squares method Television

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Null-Space Smoothing Of Tomographic images Using TV Norm Minimization

Null-Space Smoothing Of Tomographic Images Using TV Norm Min...

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IEEE Nuclear Science Symposium / Medical Imaging conference / Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD)

作者： Smith, Bruce Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX USA

ISBN: (纸本)9781509016426

Smoothing is desirable in tomographic imaging when it reduces the effects of noise in the data and is undesirable when it smooths a small feature such as a tumor or a lesion so much that they become undetectable. Linear algebra can be used to identify a significant problem associated with reconstruction from incomplete data set;namely, the rank of the resulting system matrix is less then full. To maximize its benefit and to minimize its harm, when smoothing is used in this case, it seems desirable to give more credence to the row-space component of the reconstruction than the null-space because the tomographic data contains only information about the row-space component of the object. The objective of the work presented here is to propose and demonstrate a method, which is called null-space smoothing, for achieving this. The Methodology used involved computer generated data. ART is used to reconstruct the row-space component of the Shepp and Logan phantom. By solving a convex optimization problem, an image in the nullspace was added to the reconstruction so that the resulting image had a minimum TV norm;thus, leaving the row-space component unchanged. It is concluded that although null-space smoothing can produce smooth images with an unchanged rowspace component, more work needs to be done in the future to demonstrate its usefulness with real data.

关键词： image reconstruction X-ray tomography reconstruction algorithms computed tomography

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Guided image reconstruction for Multi-Tracer PET

Guided Image Reconstruction for Multi-Tracer PET

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Sam Ellis Andrew Mallia Colm J. McGinnity Gary J. R. Cook Andrew J. Reader School of Biomedical Engineering and Imaging Sciences King’s College London UK

Scanning a patient with two or more PET radiotracers provides complementary imaging information provided by the different tracers. Invariably, one of the datasets will provide a higher quality image than the others due to a number of possible reasons, such as i) the positron energy of the radioisotope used, ii) the contrast of the tracer uptake, iii) the specificity of the tracer uptake, or iv) the quantity of injected activity and the total detected counts. This work proposes use of a higher quality PET image (the prior) to guide the reconstruction of another, lower quality PET dataset to help compensate for the reduced image quality. The prior image is used to calculate the a priori similarities between each voxel and its neighbours. Similarity is quantified using a patchbased Gaussian kernel modulated by spatial distances between voxels. A patch-based sparsification step is also included to reduce the number of non-zero similarities. The second dataset is then reconstructed with a weighted quadratic prior using these similarities as spatially-variant weights. This method penalises intensity differences between voxel pairs in accordance with those which are similar in the prior. The proposed methodology has been tested for [ 18 F] fluorodeoxyglucose (FDG)/[ 11 C] methionine (MET) paired datasets. In a 3D simulation study the FDGguided MET reconstruction produced images with lower wholebrain error levels compared to both unregularised maximum likelihood expectation-maximisation and an unguided quadratically penalised method. These improvements were also observed for real data from a patient who had undergone scans with these two tracers, where noise reduction and greater anatomical detail were attained using the FDG-guided MET reconstruction. These results suggest that using one PET tracer to guide the reconstruction of another is both feasible and potentially beneficial. Future work will require hyperparameter optimisation and further application-specific validati

关键词： image reconstruction Positron emission tomography image edge detection Kernel Attenuation image quality

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Accurate image reconstruction of Few-view Ptychrography X-ray Computed Tomography

Accurate Image Reconstruction of Few-view Ptychrography X-ra...

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IEEE International conference on Information and Automation (ICIA)

作者： Fu, J. Wang, J. Z. Beijing Univ Aeronaut & Astronaut Sch Mech Engn & Automat 37 Xueyuan Rd Beijing 100191 Peoples R China Beijing Univ Aeronaut & Astronaut Res Ctr Digital Radiat Imaging 37 Xueyuan Rd Beijing 100191 Peoples R China

ISBN: (纸本)9781509041022

Ptychrograhic x-ray computed tomography (PX-CT) is a novel analysis tool in materials science. It is based on the coherent diffraction and enables the non-destructive observation of the internal structures of the specimen at the nano-scale. Few-view PX-CT can permit rapid scanning with a reduced amount of dataset and has a great potential on material performance evaluation and non-destructive testing. There are often challenges for the image reconstruction in few-view PX-CT because of the insufficient projection data. In this paper, an accurate reconstruction method is developed and investigated for few-view PX-CT. It is based on an algebraic iteration reconstruction technique, which minimizes the image total variation and permits accurate tomographic imaging with less data. The numerical results demonstrate that the presented method can handle incomplete projection data in few-view PX-CT. It will be helpful for PX-CT applications in materials science.

关键词： X-ray coherent diffraction imaging Computed tomography Ptychrography Few-view imaging image reconstruction

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Advanced photoacoustic image reconstruction using the k-Wave toolbox

Advanced photoacoustic image reconstruction using the k-Wave...

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conference on Photons Plus Ultrasound - Imaging and Sensing

作者： Treeby, B. E. Jaros, J. Cox, B. T. UCL Dept Med Phys & Biomed Engn London WC1E 6BT England Brno Univ Technol Fac Informat Technol CS-61090 Brno Czech Republic

ISBN: (纸本)9781628419429

Reconstructing images from measured time domain signals is an essential step in tomography-mode photoacoustic imaging. However, in practice, there are many complicating factors that make it difficult to obtain high-resolution images. These include incomplete or undersampled data, filtering effects, acoustic and optical attenuation, and uncertainties in the material parameters. Here, the processing and image reconstruction steps routinely used by the Photoacoustic Imaging Group at University College London are discussed. These include correction for acoustic and optical attenuation, spatial resampling, material parameter selection, image reconstruction, and log compression. The effect of each of these steps is demonstrated using a representative in vivo dataset. All of the algorithms discussed form part of the open-source k-Wave toolbox (available from http://***).

关键词： Signal attenuation image compression Acoustics image processing reconstruction algorithms Visibility In vivo imaging Photoacoustic imaging 3D image reconstruction image filtering image quality Tomography

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Registration of Developmental image Sequences with Missing data 29

Registration of Developmental Image Sequences with Missing D...

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29th IEEE conference on Computer Vision and Pattern Recognition (CVPR)

作者： Csapo, Istvan Shi, Yundi Sanchez, Mar Styner, Martin Niethammer, Marc Univ N Carolina Chapel Hill NC 27514 USA Emory Univ Atlanta GA 30322 USA

ISBN: (纸本)9781509014378

Longitudinal image registration is commonly used to establish spatial correspondence between images when investigating temporal changes in brain morphology. Most image registration methods have been developed to align images that are similar in appearance or structure. If such similarity is not given (e.g., in the case of neurodevelopmental studies, which is the target application of this paper), (i) local similarity measures, (ii) metamorphosis approaches, or (iii) methods modeling longitudinal intensity change can be used. Methods modeling longitudinal intensity change have the advantage of not treating images as independent static samples. However, missing or incomplete data can lead to poor model estimation and, in turn, poor registration. Therefore, incomplete longitudinal data sets are often excluded from analysis. Here, we propose a method to build a longitudinal atlas of intensity change and incorporate it as a prior into an existing model-based registration method. We show that using the prior can guide the deformable registration of longitudinal images of brain development with missing data and produce comparable registration results to complete data sets.

关键词： image registration

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Efficient Volumetric Fusion of Airborne and Street-Side data for Urban reconstruction 23

Efficient Volumetric Fusion of Airborne and Street-Side Data...

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23rd International conference on Pattern Recognition (ICPR)

作者： Bodis-Szomoru, Andras Riemenschneider, Hayko Van Gool, Luc Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland

ISBN: (纸本)9781509048472

Airborne acquisition and on-road mobile mapping provide complementary 3D information of an urban landscape: the former acquires roof structures, ground, and vegetation at a large scale, but lacks the facade and street-side details, while the latter is incomplete for higher floors and often totally misses out on pedestrian-only areas or undriven districts. In this work, we introduce an approach that efficiently unifies a detailed street-side Structure-from-Motion (SfM) or Multi-View Stereo (MVS) point cloud and a coarser but more complete point cloud from airborne acquisition in a joint surface mesh. We propose a point cloud blending and a volumetric fusion based on ray casting across a 3D tetrahedralization (3DT), extended with data reduction techniques to handle large datasets. To the best of our knowledge, we are the first to adopt a 3DT approach for airborne/streetside data fusion. Our pipeline exploits typical characteristics of airborne and ground data, and produces a seamless, watertight mesh that is both complete and detailed. Experiments on 3D urban data from multiple sources and different data densities show the effectiveness and benefits of our approach.

关键词： Three-dimensional displays Surface reconstruction image reconstruction Atmospheric modeling Mobile communication Laser radar Noise measurement

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Properties of the Ellipse-Line-Ellipse Trajectory with Asymmetrical Variations

Properties of the Ellipse-Line-Ellipse Trajectory with Asymm...

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conference on Medical Imaging - Physics of Medical Imaging

作者： Guo, Zijia Noo, Frederic Maier, Andreas Lauritsch, Guenter Univ Utah Dept Radiol & Imaging Sci Utah Ctr Adv Imaging Res Salt Lake City UT 84112 USA Univ Erlangen Nurnberg Pattern Recognit Lab D-91054 Erlangen Germany Siemens Healthcare GmbH Erlangen Germany

ISBN: (纸本)9781510600188

Three-dimensional cone-beam (CB) imaging using a multi-axis floor-mounted (or ceiling-mounted) C-arm system has become an important tool in interventional radiology. This success motivates new developments to improve image quality. One direction in which advancement is sought is the data acquisition geometry and related CB artifacts. Currently, data acquisition is performed using the circular short-scan trajectory, which yields limited axial coverage and also provides incomplete data for accurate reconstruction. To improve the image quality, as well as to increase the coverage in the longitudinal direction of the patient, we recently introduced the ellipse line -ellipse trajectory and showed that this trajectory provides full R-line coverage within the field-of-view, which is a key property for accurate reconstruction from truncated data. An R-line is any segment of line that connects two source positions. Here, we examine how the application of asymmetrical variations to the definition of the ELE trajectory impacts the R-line coverage. This question is significant to understand how much flexibility can be used in the implementation of the ELE trajectory, particularly to adapt the scan to patient anatomy and imaging task of interest. Two types of asymmetrical variations, called axial and angular variations, are investigated.

关键词： data acquisition Imaging systems image quality image-guided intervention 3D image processing image segmentation Medicine 3D acquisition image restoration reconstruction algorithms Computed tomography Cones

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