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conference on Holography and Diffractive Optics III

作者： Tang, Xiaochun Gao, Yiqing Nanchang Hangkong Univ Minist Educ China Key Lab Nondestruct Test Nanchang 330063 Jiangxi Peoples R China

ISBN: (纸本)9780819470072

In order to improve the quality and solve the problem of low speed of image reconstruction in the traditional optical computerized tomography (OCT) when the data acquired is incomplete projection, the multiple constrained of genetic algorithm based on algebraic iterative was proposed. Generally speaking, under the condition of multiple-objective optimization, the common extreme point for all the objective functions doesn't exist. So we can achieve the preferable compromise in the contradictions of multiple objectives. In this article, there are three constrained conditions. The first one is the maximum entropy criterion which is used mostly to solve the problem of OCT image reconstruction when the data acquired is incomplete projection recently. The second one is the minimum criteria of peak value which is introduced to suppress noise effectively and ensure the gliding property of the image reconstruction, because of the first one leading to noise amplification during the iterative process. The last constrained condition is the minimum criteria of the difference between the projection again of image reconstruction and the original projection. The concept of penalize-function is introduced into the genetic algorithm, which would transform the constrained optimization problem to unconstrained. It is clearly demonstrated from the experiment results that the algorithm reconstruction technique can efficiently improve the quality of images reconstruction of the incomplete projection data.

关键词： incomplete projection data image reconstruction multiple constrained genetic algorithm

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Multi-spectral intensity diffraction tomography

Multi-spectral intensity diffraction tomography

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conference on image reconstruction from incomplete data v

作者： Anastasio, Mark A. Xu, Qiaofeng Shi, Daxin IIT Dept Biomed Engn Med Imaging Res Ctr Chicago IL 60616 USA Toshiba Med Res Inst USA Inc Vernon Hills IL USA

ISBN: (纸本)9780819472960

Intensity diffraction tomography (I-DT) is a, non-interferometric imaging method for reconstructing the complex-valued refractive index distribution of a, weakly scattering object. The original formulation of I-DT requires measurement of two in-line intensity measurements on parallel detector planes at each tomographic view angle. In this work, a reconstruction theory for multi-spectral is established and investigated for use with single material objects whose dispersion characteristics are known a priori. Unlike other I-DT methods, the temporal frequency of the illuminating plane-wave represents the degree-of-freedom of the imaging system that is varied to acquire two independent intensity measurements on a fixed detector-plane. Moreover, the proposed method accounts for object dispersion.

关键词： Diffraction tomography phase-contrast tomography three-dimensional image reconstruction

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Superresolution capabilities of 3D optical filters

Superresolution capabilities of 3D optical filters

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conference on image reconstruction from incomplete data v

作者： Fiddy, Michael A. Testorf, Markus E. Dartmouth Coll Thayer Sch Engn 8000 Cummings Hall Hanover NH 03755 USA Univ N Carolina Charlotte NC 28223 USA

ISBN: (纸本)9780819472960

Multichannel sampling strategies have been considered for a number of applications including feature specific imaging, and digital superresolution. Typically, channel coding is accomplished with a thin modulating mask, either in the focal plane, or in the aperture of the imaging system. In this contribution, we extend Hie concept of multichannel imaging to systems by suggesting the use of 3D structures for channel coding. A single pixel camera design and the single scattering approximation are used to obtain a Fourier space interpretation of 3D filters. The k-space analysis indicates that the dispersion relation of propagating plane wave modes set severe constraints if 3D filters are used for channel coding. We relate this to the broader questions about the fundamental limits of optical and computational imaging and propose 3D filters for wavelength coding and superresolution applications.

关键词： Computational Imaging Resolution Enhancement image reconstruction Multiple image Frames volume Holograms

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Space-time Surface reconstruction Using Incompressible Flow

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ACM TRANSACTIONS ON GRAPHICS 2008年第5期27卷 1–10页

作者： Sharf, Andrei Alcantara, Dan A. Lewiner, Thomas Greif, Chen Sheffer, Alla Amenta, Nina Cohen-Or, Daniel Univ Calif Davis Davis CA 95616 USA PUC Rio Janeiro Rio De Janeiro Brazil Univ British Columbia Vancouver BC V5Z 1M9 Canada Tel Aviv Univ Tel Aviv Israel

We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time solid, made up of spatial slices, each of which is a three-dimensional solid bounded by a watertight manifold. The motion of the object is described as an incompressible flow of material through time. We optimize the flow so that the distance material moves from one time frame to the next is bounded, the density of material remains constant, and the object remains compact. This formulation overcomes deficiencies in the acquired data, such as persistent occlusions, errors, and missing frames. We demonstrate the performance of our flow-based technique by reconstructing coherent sequences of watertight models from incomplete scanner data.

关键词： reconstruction space-time volumetric techniques

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A preliminary investigation of using prior information for potentially improving image reconstruction in few-view CT

A preliminary investigation of using prior information for p...

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Medical Imaging 2008 conference

作者： Cho, Seungryong Sidky, Emil Y. Bian, Junguo Pelizzari, Charles A. Pan, Xiaochuan Univ Chicago Dept Radiol Chicago IL 60637 USA Univ Chicago Dept Radiat & Cellular Oncol Chicago IL 60637 USA

ISBN: (纸本)9780819470973

There exists a strong need to reconstruct computed tomographic (CT) images with practically useful quality from a small number of projections in image-guided radiation therapy: for lowering radiation dose delivered to the subject, for shortening the imaging time, and for reducing the imaging-configuration complexity. We have recently developed an iterative image reconstruction algorithm based on total-variation (Tv) minimization from incomplete projection data in CT. In numerical studies with a variety of incomplete projection-data sets including truncated data, reduced scan range, and sparse sampling, the developed algorithm seems to yield reasonable reconstruction, as compared to some of the existing algorithms, such as algebraic reconstruction technique (ART) and expectation minimization (EM). The Tv-based algorithm begins in general with a uniform image as an initial guess, and goes through iteration steps to minimize the image Tv subject to satisfying the given incomplete projection data. In image-guided radiation therapy (IGRT), a patient usually undergoes CT scanning for treatment. planning, which can provide the reference image for image guidance. Therefore, we propose a Tv-based algorithm with a priori information in few-view CT for IGRT, in an attempt to further reduce the number of projections needed for image reconstruction from what the Tv-based algorithm uses when no a priori information is included. In this work, we report the initial results of a preliminary numerical study that we have conducted to demonstrate this approach.

关键词： reconstruction algorithms Computed tomography Expectation maximization algorithms image restoration Algorithm development Radiotherapy CT reconstruction image quality Detection and tracking algorithms image registration

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Inversion of strongly scattered data: shape and permittivity recovery

Inversion of strongly scattered data: shape and permittivity...

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conference on image reconstruction from incomplete data v

作者： Shahid, U. Fiddy, M. A. Testorf, M. E. Univ N Carolina Ctr Optoelect & Opt Commun Charlotte NC 28223 USA Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)9780819472960

Reconstructing an object from scattered field data has always been very challenging, especially when dealing with strong scatterers. Several techniques have been proposed to address this problem but either they fail to provide a good estimate of the object or they are computationally very expensive. We have proposed a straightforward non-linear signal processing method in which we first process the scattered field data to generate a minimum phase function in the object domain. This is accomplished by adding a reference wave whose amplitude and phase satisfy certain conditions. Minimum-phase functions are causal transforms and their phase is continuous in the interval -pi and +pi, i.e. it is always unwrapped. Following this step, we compute the Fourier transform of the logarithm of this minimum phase function, referred to as its cepstrum. In this domain one can filter cepstral frequencies arising from the object from those of the scattered field. Cepstral data arc meaningless for non-minimum phase functions because of phase wraps. We apply low pass filters in the cepstral domain to isolate information about the object and then perform an inverse transform and exponentiation. We have applied this technique to measured data provided by Institut Fresnel (Marseille, France) and investigated in a systematic way the dependence of the approach on the properties of the reference wave and filter. We show that while being a robust method, one can identify optimal parameters for the reference wave that result in a good reconstruction of a penetrable, strongly scattering permittivity distribution.

关键词： inverse scattering minimum phase condition homomorphic filtering imaging

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Markerless garment capture

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ACM TRANSACTIONS ON GRAPHICS 2008年第3期27卷 99-1-99-9-0页

作者： Bradley, Derek Popa, Tiberiu Sheffer, Alla Heidrich, Wolfgang Boubekeur, Tamy Univ British Columbia Vancouver BC V5Z 1M9 Canada TU Berlin Berlin Germany

A lot of research has recently focused on the problem of capturing the geometry and motion of garments. Such work usually relies on special markers printed on the fabric to establish temporally coherent correspondences between points on the garment's surface at different times. Unfortunately, this approach is tedious and prevents the capture of off-the-shelf clothing made from interesting fabrics. In this paper, we describe a marker-free approach to capturing garment motion that avoids these downsides. We establish temporally coherent parameterizations between incomplete geometries that we extract at each timestep with a multiview stereo algorithm. We then fill holes in the geometry using a template. This approach, for the first time, allows us to capture the geometry and motion of unpatterned, off-the-shelf garments made from a range of different fabrics.

关键词： object scanning/acquisition cloth modeling image processing motion capture surface reconstruction

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incomplete points cloud data surface reconstruction based on neural network

Incomplete points cloud data surface reconstruction based on...

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4th International conference on Intelligent Information Hiding and Multimedia Signal Processing

作者： Wu Xue-mei Li Gui-xian Zhao Wei-min Harbin Inst Technol Sch Mech & Elect Harbin 150001 Heilongjiang Pr Peoples R China Daquing Univ Dept Engn Mech Daqing 163318 Heilongjiang Peoples R China

ISBN: (纸本)9780769532783

Neural network arithmetic was employed in incomplete points cloud data surface reconstruction, Radial basis function neural network and simulated annealing arithmetic was combined. The new arithmetic can approach any nonlinear function by arbitrary precision, and also keep the network from getting into local minimum. Global optimization feature of simulated annealing was employed to adjust the network weights. MATLAB program was compiled, experiments on incomplete points cloud data have been done employing this arithmetic, the result shows that this arithmetic can efficiently approach the surface with 10(-4) mm error precision, and also the learning speed is quick and the reconstruction surface is smooth. Different methods have been employed to do surface reconstruction in comparison, the results illustrate the error employed algorithmic proposed in the paper is little and converge speed is quick.

关键词： Surface reconstruction Artificial neural networks image reconstruction Simulated annealing Training Meteorology Radial basis function networks

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Realtime visualization of monocular data for 3D reconstruction

Realtime visualization of monocular data for 3D reconstructi...

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5th Canadian conference on Computer and Robot vision

作者： Rachmielowski, Adam Birkbeck, Neil Jagersand, Martin Cobzas, Dana Univ Alberta CS Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9780769531533

Methods for reconstructing photorealistic 3D graphics models from images or video are appealing applications of computer vision. Such methods rely on good input image data, but the lack-of user feedback during image acquisition often leads to incomplete or poorly sampled reconstruction results. We describe a video-based system that constructs and visualizes a coarse graphics model in real-time and automatically saves a set of images appropriate for later off-line dense reconstruction. visualization of the model during image acquisition allows the operator to interactively verify that an adequate set of input images has been collected for the modeling task, while automatic image selection keeps storage requirements to a minimum. Our implementation uses real-time monocular SLAM to compute and continuously keep extending a 3D model, augments this with key-frame selection for storage, surface modelling, and on-line rendering of the current structure textured from a selection of key-frames. This rendering gives an immediate and intuitive view of both the geometry and if suitable viewpoints of texture images have already been captured.

关键词： image acquisition

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Convex Ultrasound image reconstruction with Log-Euclidean Priors

Convex Ultrasound Image Reconstruction with Log-Euclidean Pr...

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30th Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Seabra, Jose Xavier, Joao Sanches, Joao Univ Tecn Lisboa Syst & Robot Inst Inst Super Tecn P-1049001 Lisbon Portugal

ISBN: (纸本)9781424418145

image reconstruction from noisy and incomplete observations is usually an ill-posed problem. A Bayesian framework may be adopted do deal with this such inverse task by well posing the reconstruction problem. In this approach, the ill poseness nature of the reconstruction is removed by minimizing a two-term energy function. The first term pushes the solution toward the data and the second regularizes the solution. A Bayesian algorithm for ultrasound image reconstruction and de-noising is proposed where an edge preserving prior is used to reduce the smoothing effect at the transitions. The prior distribution is based on log-Euclidean potential functions that are particular suitable in reconstruction problems under the constraint of positivity, that is, when the unknowns to be estimated should be positive, which is the case, where the noisy observations are modeled by a Rayleigh distribution. In this paper, the reconstruction procedure is formulated as the optimization of a convex function and a Newton method is adopted to obtain the minimizer. This strategy guarantees a convergence to the global minimum in a small number of iterations. Experimental results, using synthetic and real medical images are shown. The proposed method produces images where speckle noise is effectively suppressed and important clinical details (organ and tissue transitions) are preserved.

关键词： Newton-Raphson method

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