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conference on image reconstruction from incomplete data vI

作者： Kieweg, Michael Gross, Herbert Sievers, Torsten Mueller, Lothar Carl Zeiss Corp Res & Technol D-73446 Oberkochen Germany Carl Zeiss Corp Res & Technol D-07745 Jena Germany

ISBN: (纸本)9780819482969

In optical systems with quite good correction, the field-dependence of aberrations often can be neglected. In low performance systems, for the application of deconvolution methods the field-dependence of the point spread function must be taken into account. However, the number of publications dealing with the topic of space-variant deconvolution in order to compensate system aberrations is quite low. In this contribution, we investigate the fundamental difficulty accompanied by space-variant deconvolution, which makes the problem ill-posed, even in the case of non-vanishing modular transfer functions and the assumption of noise-free imaging. The spatial frequencies of the image spectrum are mixed depending on the field-dependencies of the optical aberrations. In general, it is therefore not possible to reconstruct the individual frequencies exactly. Some discrete examples with a non unique solution are presented. For the 2D case, we will show and investigate how the most popular algorithms deal with this fundamental problem for different typical types of optical aberrations. Depending on the aberration, the computational results for those algorithms differ from very good results to images with artifacts. The Lucy Richardson method, which is often recommended in the case of space-invariant image reconstruction since it may even reconstruct frequencies above the cut off frequency, provides poor results for unsymmetrical space-variant aberrations like Coma or a simple Tilt. However, we will show that a simpler method like the Landweber algorithm is better suited to deal with those kinds of aberrations.

关键词： Space-variant deconvolution image restoration optical aberrations

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Classification of cryo electron microscopy images, noisy tomographic images recorded with unknown projection directions, by simultaneously estimating reconstructions and application to an assembly mutant of Cowpea Chlorotic Mottle virus and portals of the bacteriophage P22

Classification of cryo electron microscopy images, noisy tom...

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conference on image reconstruction from incomplete data vI

作者： Lee, Junghoon Zheng, Yili Yin, Zhye Doerschuk, Peter C. Johnson, John E. Johns Hopkins Univ Elect & Comp Engn Baltimore MD 21218 USA Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA 94720 USA Gen Elect Global Res Niskayuna 12309 NY USA Scripps Res Inst Dept Mol Biol La Jolla CA 92037 USA

ISBN: (纸本)9780819482969

Cryo electron microscopy is frequently used on biological specimens that show a mixture of different types of object. Because the electron beam rapidly destroys the specimen, the beam current is minimized which leads to noisy images (SNR substantially less than 1) and only one projection image per object (with an unknown projection direction) is collected. For situations where the objects can reasonably be described as coming from a finite set of classes, an approach based on joint maximum likelihood estimation of the reconstruction of each class and then use of the reconstructions to label the class of each image is described and demonstrated on two challenging problems: an assembly mutant of Cowpea Chlorotic Mottle virus and portals of the bacteriophage P22.

关键词： statistical image classification statistical inverse problem statistical signal reconstruction tomography cryo electron microscopy virus structure Cowpea Chlorotic Mottle virus portal of Bacteriophage P22

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Imposing spatio-temporal support in magnetic resonance angiographic imaging

Imposing spatio-temporal support in magnetic resonance angio...

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conference on image reconstruction from incomplete data vI

作者： Bones, Philip J. vafadar, Bahareh Watts, Richard Wu, Bing Univ Canterbury Dept Elect & Comp Engn Computat Imaging Grp Christchurch New Zealand Univ Canterbury Dept Phys & Astron Christchurch New Zealand Duke Univ Brain Imaging & Analysis Ctr Sch Med Durham NC 27708 USA

ISBN: (纸本)9780819482969

A method to improve time resolution in 3D contrast-enhanced magnetic resonance angiography (CE-MRA) is proposed. A temporal basis based on prior knowledge of the contrast flow dynamics is applied to a sequence of image reconstructions. In CE-MRA a contrast agent (gadolinium) is injected into a peripheral vein and MR data is acquired as the agent arrives in the arteries and then the veins of the region of clinical interest. The acquisition extends over several minutes. Information is effectively measured in 3D k-space (spatial frequency space) one line at-a-time. That line may be along a Cartesian grid line in k-space, a radial line or a spiral trajectory. A complete acquisition comprises many such lines but in order to improve temporal resolution, reconstructions are made from only partial sets of k-space data. By imposing a basis for the temporal changes, based on prior expectation of the smoothness of the changes in contrast concentration with time, it is demonstrated that a significant reduction in artifacts caused by the under-sampling of k-space can be achieved. The basis is formed from a set of gamma variate functions. Results are presented for a simulated set of 2D spiral-sampled CE-MRA data.

关键词： Magnetic resonance imaging data acquisition Arteries Temporal resolution Angiography Signal to noise ratio Gadolinium image quality veins Magnetism

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Research of the image reconstruction from incomplete Projection data Based on the Homotopy Mapping

Research of the Image Reconstruction from Incomplete Project...

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2nd International Asia conference on Informatics in Control, Automation and Robotics (CAR)

作者： Li Fei Pan Jin-Xiao North Univ China Coll Sci Dept Math Taiyuan Peoples R China North Univ China Natl Key Lab Elect Measurement Technol Taiyuan Peoples R China

ISBN: (纸本)9781424451944

Multi-objective optimization reconstruction algorithm is one of the main methods to solve the limited angle image reconstruction. However we have great difficulty in selecting the right parameter reasonably because there is not only one objective function. So we give a new method to choose the parameter which was called homotopy parameter based on the theory of homotopy in this paper. Finally, the simulations were carried out to verify the proposed strategy, and the simulation results show that this algorithm is superior to the conventional multi-objective optimization methods in many aspects, such as less reconstruction errors, higher smoothness and gray value resolution.

关键词： multi-objective optimization limited angle image reconstruction homotopy parameter

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Rethinking image Registration on Customizable Hardware

Rethinking Image Registration on Customizable Hardware

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conference on image reconstruction from incomplete data vI

作者： Bowman, David Tahtali, Murat Lambert, Andrew UNSW ADFA Sch Engn & IT Canberra ACT 2600 Australia

ISBN: (纸本)9780819482969

image registration is one of the most important tasks in image processing and is frequently one of the most computationally intensive. In cases where there is a high likelihood of finding the exact template in the search image, correlation-based methods predominate. Presumably this is because the computational complexity of a correlation operation can be reduced substantially by transforming the task into the frequency domain. Alternative methods such as minimum Sum of Squared Differences (minSSD) are not so tractable and are normally disfavored. This bias is justified when dealing with conventional computer processors since the operations must be conducted in an essentially sequential manner however we demonstrate it is normally unjustified when the processing is undertaken on customizable hardware such as FPGAs where tasks can be temporally and/or spatially parallelized. This is because the gate-based logic of an FPGA is better suited to the tasks of minSSD i.e. signed-addition hardware can be very cheaply implemented in FPGA fabric, and square operations are easily implemented via a look-up table. In contrast, correlation-based methods require extensive use of multiplier hardware which cannot be so cheaply implemented in the device. Even with modern DSP-oriented FPGAs which contain many "hard" multipliers we experience at least an order of magnitude increase in the number of minSSD hardware modules we can implement compared to cross-correlation modules. We demonstrate successful use and comparison of techniques within an FPGA for registration and correction of turbulence degraded images.

关键词： image Registration FPGA Cross Correlation Minimum Sum of Squared Differences

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SU-E-J-177: Improved reconstruction Algorithm for Tomosynthesis Plus Few Discrete Projections

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Medical Physics 2011年第6PART10期38卷 3484-3484页

作者： Y Wei M McKee A Baydush Wake Forest University School of Medicine Winston Salem NC

Purpose: Investigations over the past few years have demonstrated some of the benefits and shortfalls of tomosynthesis in radiation therapy for patient positioning or dose tracking. Tomosynthesis generates excellent image quality in one reconstruction plane; however, there is a loss of edge and frequency information in the additional planes due to the spatial incompleteness of the projection data. In this study, we investigate the results of a new discrete frequency interpolation technique (DFIT), which is used to incorporate tomosynthesis limited arc projection data and three additional “filling” projections. Methods: For the initial investigations, we simulated a Shepp-Logan phantom with parallel beam geometry to generate 93 projections. 90 of these projections were over a tomosynthetic arc at one projection per degree. The remaining three projections were generated to fill in the next 90 degrees evenly (i.e. 22.5, 45, and 67.5 degrees from the end of the arc) to help “fill in” the incomplete data. Simple filtered backprojection (FBP) results show no improvement as FBP is designed for uniform distribution of projections. Per the projection slice theorem, the tomosynthesis data fills in a portion of the frequency plane. The remaining sparsely sampled area of the frequency plane is filled using linear interpolation from the end arc projections and the 3 discrete projections. The DFIT image is the sum of the FBP image and the inverse Fourier transform of the interpolated frequencies Results: The images by traditional FBP and DFIT are compared visually and using line profile plots. Additionally, contrast results are examined. The DFIT images show improved edge delineation in the usual tomosynthesis “blurred” direction and improves reconstructed contrast. Conclusions: The addition of limited “filling” discrete projections and DFIT can be used to improve the reconstruction accuracy and quality of short arc imaging. Research supported by Nucletron, B.v.

关键词： Digital tomosynthesis mammography Medical imaging image reconstruction Interpolation Medical image reconstruction Dosimetry Radiation therapy Fourier transforms Medical image quality

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Metal Artifact Reduction in Computed Tomography by Constrained Optimization

Metal Artifact Reduction in Computed Tomography by Constrain...

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conference on Medical Imaging - Physics of Medical Imaging

作者： Zhang, Xiaomeng Wang, Jing Xing, Lei Stanford Univ Dept Elect Engn Stanford CA 94305 USA Stanford Univ Dept Radiat Oncol Stanford CA 94305 USA

ISBN: (纸本)9780819480231

Computed tomography (CT) streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. An effective and robust algorithm is highly desirable to minimize metal artifacts and achieve clinically acceptable CT images. In this work, the raw projection data is viewed as "incomplete" in the presence of metal shadows. Shape and location of metal objects are automatically identified and used as prior knowledge for accurate segmentation of metal shadows in projection domain. An iterative algorithm based on constrained optimization is then used for the image reconstruction. This algorithm minimizes a quadratic penalized smoothness measure function of the image, subject to the constraint that the estimated projection data is within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The constrained minimization problem is optimized through the combination of projection onto convex sets (POCS) and steepest gradient descent of the smoothness measure objective. Digital phantom study shows that the proposed constrained optimization algorithm has superior performance in reducing metal artifacts, suppressing noise and improving soft-tissue visibility. Some comparisons are performed with the filtered-back-projection (FBP), FDK, POCS and constrained optimization with total-variation (Tv) objective. Although the algorithm is presented in the context of metal artifacts, it can be generated to image reconstruction from incomplete projections caused by limited angular range or low angular sampling rate in both 2D and 3D cases.

关键词： computed tomography (CT) metal artifacts image reconstruction optimization

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Comparison of reconstruction algorithms for sparse-array detection photoacoustic tomography

Comparison of reconstruction algorithms for sparse-array det...

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conference on Photons Plus Ultrasound - Imaging and Sensing 2010

作者： Chaudhary, G. Roumeliotis, M. Carson, J. J. L. Anastasio, M. A. IIT Med Imaging Res Ctr Dept Elect & Comp Engn Chicago IL 60616 USA IIT Med Imaging Res Ctr Dept Biomed Engn Chicago IL 60616 USA St Josephs Hlth Care Lawson Hlth Res Inst Imaging Program London ON N6A 4V2 Canada Univ West Ontario Dept Med Biophys London ON N6A 5C1 Canada

ISBN: (纸本)9780819479600

A photoacoustic tomography (PAT) imaging system based on a sparse 2D array of detector elements and an iterative image reconstruction algorithm has been proposed, which opens the possibility for high frame-rate 3D PAT. The efficacy of this PAT implementation is highly influenced by the choice of the reconstruction algorithm. In recent years, a variety of new reconstruction algorithms have been proposed for medical image reconstruction that have been motivated by the emerging theory of compressed sensing. These algorithms have the potential to accurately reconstruct sparse objects from highly incomplete measurement data, and therefore may be highly suited for sparse array PAT. In this context, a sparse object is one that is described by a relatively small number of voxel elements, such as typically arises in blood vessel imaging. In this work, we investigate the use of a gradient projection-based iterative reconstruction algorithm for image reconstruction in sparse-array PAT. The algorithm seeks to minimize an l(1)-norm penalized least-squares cost function. By use of computer-simulation studies, we demonstrate that the gradient projection algorithm may further improve the efficacy of sparse-array PAT.

关键词： Photoacoustic tomography sparse-array photoacoustic tomography image reconstruction

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Evaluation and optimization of the maximum-likelihood approach for image reconstruction in digital breast tomosynthesis

Evaluation and optimization of the maximum-likelihood approa...

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conference on Medical Imaging - Physics of Medical Imaging

作者： Jerebko, Anna K. Mertelmeier, Thomas Siemens AG Healthcare D-91050 Erlangen Germany

ISBN: (纸本)9780819480231

Digital Breast Tomosynthesis* (DBT) suffers from incomplete data and poor quantum statistics limited by the total dose absorbed in the breast. Hence, statistical reconstruction assuming the photon statistics to follow a Poisson distribution may have some advantages. This study investigates state-of-art iterative maximum likelihood (ML) statistical reconstruction algorithms for DBT and compares the results with simple backprojection (BP), filtered backprojection (FBP), and iFBP (FBP with filter derived from iterative reconstruction). The gradient-ascent and convex optimization variants of the transmission ML algorithm are evaluated with phantom and clinical data. Convergence speed is very similar for both iterative statistical algorithms and after approximately 5 iterations all significant details are well displayed, although we notice increasing noise. We found empirically that a relaxation factor between 0.25 and 0.5 provides the optimal trade-off between noise and contrast. The ML-convex algorithm gives smoother results than the ML-gradient algorithm. The low-contrast CNR of the ML algorithms is between CNR for simple backprojection (highest) and FBP (lowest). Spatial resolution of iterative statistical and iFBP algorithms is similar to that of FBP but the quantitative density representation better resembles conventional mammograms. The iFBP algorithm provides the benefits of statistical iterative reconstruction techniques and requires much shorter computation time.

关键词： tomosynthesis iterative reconstruction statistical reconstruction filtered backprojection breast imaging mammography

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Sensor Saturation in Fourier Multiplexed Imaging

Sensor Saturation in Fourier Multiplexed Imaging

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23rd IEEE conference on Computer vision and Pattern Recognition (CvPR)

作者： Wetzstein, Gordon Ihrke, Ivo Heidrich, Wolfgang Univ British Columbia Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9781424469840

Optically multiplexed image acquisition techniques have become increasingly popular for encoding different exposures, color channels, light fields, and other properties of light onto two-dimensional image sensors. Recently, Fourier-based multiplexing and reconstruction approaches have been introduced in order to achieve a superior light transmission of the employed modulators and better signal-to-noise characteristics of the reconstructed data. We show in this paper that Fourier-based reconstruction approaches suffer from severe artifacts in the case of sensor saturation, i.e. when the dynamic range of the scene exceeds the capabilities of the image sensor. We analyze the problem, and propose a novel combined optical light modulation and computational reconstruction method that not only suppresses such artifacts, but also allows us to recover a wider dynamic range than existing image-space multiplexing approaches.

关键词： image sensors

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