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Understanding stochastic biological macromolecular complexes by estimating a mechanical model via statistical mechanics from cryo electron microscopy images

Understanding stochastic biological macromolecular complexes...

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conference on image reconstruction from incomplete data vI

作者： Wang, Kang Doerschuk, Peter C. Cornell Univ Ithaca NY 14853 USA

ISBN: (纸本)9780819482969

Cryo electron microscopy imaging experiments can lead to stochastic models for biological macromolecular complexes. However, interpreting the statistical variability is difficult. In some situations, the variability in the original complexes is due to primarily thermal fluctuations which are snap frozen in place by the preparation of the specimen. In this case the images are images of samples of the equilibrium statistical mechanics ensemble of the complex. Based on representing the complex by a lattice spring-mass mechanical model, an estimation problem for determining the masses and spring constants is described and demonstrated on synthetic data.

关键词： equilibrium statistical mechanics 3-D image understanding cryo electron microscopy virus structure

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An image reconstruction Model and Hybrid Algorithm for Limited-angle Projection data

An Image Reconstruction Model and Hybrid Algorithm for Limit...

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IEEE International conference on Bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Gao Hongxia Luo Yinghao Chen Kewei Ma Ge Wu Lixuan S China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Guangdong Peoples R China S China Univ Technol Minist Educ Engn Res Ctr Precis Elect Mfg Equipment Guangzhou 510641 Guangdong Peoples R China

ISBN: (纸本)9781467367981

More and more applications in industrial or medical CT have to adopt limited-angle projection data, such as restricted scanning, decreasing radiation dose and so on. Traditional reconstruction methods for incomplete projection data, including analytic reconstruction and iterative reconstruction, can't meet the demand of limited-angle reconstruction. To deal with Tv reconstruction model's imbalance in reconstructing image information of different direction, this paper proposes a reconstruction model and its corresponding hybrid algorithm, which utilize horizontal direction gradient to assist Tv reconstruction in vertical direction. Experiments results demonstrate the proposed method's effectiveness and performance in image reconstruction from limited-angle projection data.

关键词： image reconstruction limited-angle projection data hybrid algorithm

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3D ROI-image reconstruction from cone-beam data

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2007年第2期580卷 866-875页

作者： Xia, Dan Cho, Seungryong Bian, Junguo Zou, Yu Sidky, Emil Y. Zuo, Niamning Pan, Xiaochuan Univ Chicago Dept Radiol Chicago IL 60637 USA Acad Sinica Inst Automat Med Imaging Lab Beijing Peoples R China

Helical and circular trajectories are expected to be adopted dominantly for data acquisition in X-ray cone-beam (CB) computed tomography (CT) imaging. However, non-conventional trajectories, such as tilted helical, saddle, circle-circle, and circle-line trajectories, may also find important applications. Therefore, accurate image reconstruction from data acquired with these non-conventional trajectories remains of practical significance. However, the non-conventional trajectories have been studied on a case-per-case basis and little effort has been made to investigate all of these trajectories on a single algorithm. Recently, there has been significant development on image reconstruction for general CB trajectories. In particular, chord-based algorithms have been developed for image reconstruction in CBCT. In this work, we investigate the chord-based algorithms, which can accommodate data containing both longitudinal and transverse truncations to a certain extent, for image reconstruction from data acquired with four different trajectories: the tilted helical, saddle, circle-circle, and circle-line trajectories. The first two represent smooth trajectories, whereas the last two are non-smooth trajectories containing kinks. The significance of the work lies not only in demonstrating the ability of the algorithm for image reconstruction from CB data but also in visualizing the reconstructible regions-of-interest (ROIs) for those general trajectories so that one can setup the scanning parameters with an appropriate guide. (c) 2007 Published by Elsevier B.v.

关键词： data acquisition

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Comparison of reconstruction algorithms for images from sparse-aperture systems

Comparison of reconstruction algorithms for images from spar...

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2nd conference on image reconstruction from incomplete data

作者： Fienup, JR Griffith, D Harrington, L Kowalczyk, AM Miller, JJ Mooney, JA Univ Rochester Inst Opt Rochester NY 14627 USA

ISBN: (纸本)0819445592

Telescopes and imaging interferometers with sparsely filled apertures can be lighter weight and less expensive than conventional filled-aperture telescopes. However, their greatly reduced MTF's cause significant blurring and loss of contrast in the collected imagery. image reconstruction algorithms can correct the blurring completely when the signal-to-noise ratio (SNR) is high, but only partially when the SNR is low. This paper compares both linear (Wiener) and nonlinear (iterative maximum likelihood) algorithms for image reconstruction under a variety of circumstances. These include high and low SNR, Gaussian noise and Poisson-noise dominated, and a variety of aperture configurations and degrees of sparsity. The quality metric employed to compare algorithms is image utility as quantified by, the National imagery Interpretability Rating Scale (NIIRS). On balance, a linear reconstruction algorithm with a power-law power-spectrum estimate performed best.

关键词： image reconstruction sparse apertures deconvolution image restoration MTF image quality Wiener filter power spectrum estimation maximum likelihood

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Superresolved image reconstruction from incomplete data

Superresolved Image Reconstruction from Incomplete Data

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conference on image reconstruction from incomplete data vII

作者： Chuang, Yi-Chen Dudley, Richard Fiddy, Michael A. Nanyang Technol Univ Sch Elect & Elect Engn 50 Nanyang Ave Singapore 639798 Singapore Univ N Carolina Dept Phys & Opt Sci Charlotte NC 28223 USA Univ N Carolina Ctr Optoelect & Opt Commun Charlotte NC 28223 USA

ISBN: (纸本)9780819492173

A finite thickness slab of a metamaterial having a refractive index close to n = -1, can be used for sub-wavelength scale imaging. In the image domain, the measured fields contain evanescent wave contributions from subwavelength scale features in the object but these have to be related to the intrinsic parameters describing the scatterer such as refractive index or permittivity. For weak scatterers there can be a simple relationship between the field distribution and the permittivity profile. However for strong (multiple) scatterers and, more importantly, for objects for which subwavelength features contribute to the scattered (near) field, there is no simple relationship between the measured data and the permittivity profile. This is a significant inverse scattering problem for which no immediate solution exists and given the metamaterial slab's limitations one cannot assume that either angle or wavelength diversity will be available to apply an inverse scattering algorithm. We consider wavelength diversity in this paper to acquire the measured data necessary to estimate a superresolved solution to the inverse scattering problem.

关键词： Metamaterials superresolution scattering inverse scattering algorithm

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Process reconstruction from incomplete and/or inconsistent data

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EUROPEAN PHYSICAL JOURNAL D 2005年第2期32卷 215-222页

作者： Ziman, T Plesch, M Buzek, v Slovak Acad Sci Res Ctr Quantum Informat Bratislava 84511 Slovakia Masaryk Univ Fac Informat Brno 60200 Czech Republic

We analyze how an action of a qubit channel (map) can be estimated from the measured data that are incomplete or even inconsistent. That is, we consider situations when measurement statistics is insufficient to determine consistent probability distributions. As a consequence either the estimation (reconstruction) of the channel completely fails or it results in an unphysical channel (i.e., the corresponding map is not completely positive). We present a regularization procedure that allows us to derive physically reasonable estimates (approximations) of quantum channels. We illustrate our procedure on specific examples and we show that the procedure can be also used for a derivation of optimal approximations of operations that are forbidden by the laws of quantum mechanics (e.g., the universal NOT gate).

关键词： Quantum mechanics Quantum communication State reconstruction, quantum tomography

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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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Characterizing heterogeneity among virus particles by stochastic 3-D signal reconstruction 8

Characterizing heterogeneity among virus particles by stocha...

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conference on image reconstruction from incomplete data vIII

作者： Xu, Nan Gong, Yunye Wang, Qiu Zheng, Yili Doerschuk, Peter C. Cornell Univ Elect & Comp Engn Ithaca NY 14850 USA Univ Calif Berkeley Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Cornell Univ Meinig Sch Biomed Engn Ithaca NY USA

ISBN: (纸本)9781628417661

In single-particle cryo electron microscopy, many electron microscope images each of a single instance of a biological particle such as a virus or a ribosome are measured and the 3-D electron scattering intensity of the particle is reconstructed by computation. Because each instance of the particle is imaged separately, it should be possible to characterize the heterogeneity of the different instances of the particle as well as a nominal reconstruction of the particle. In this paper, such an algorithm is described and demonstrated on the bacteriophage Hong Kong 97. The algorithm is a statistical maximum likelihood estimator computed by an expectation maximization algorithm implemented in Mat lab software.

关键词： 3-D image reconstruction statistical image processing maximum likelihood estimation expectation maximization algorithm structural biology virus Hong Kong 97

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Feasibility study for image reconstruction in circular digital tomosynthesis (CDTS) from limited-scan angle data based on compressed-sensing theory

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2015年 777卷 161-166页

作者： Park, Yeonok Je, Uikyu Cho, Hyosung Hong, Daeki Park, Chulkyu Cho, Heemoon Choi, Sungil Woo, Taeho Yonsei Univ Dept Radiol Sci iTOMO Wonju 220710 South Korea Yonsei Univ VYSION Res Ctr Wonju 220710 South Korea

In this work, we performed a feasibility study for image reconstruction in a circular digital tomosynthesis (CDTS) from limited-scan angle data based on compressed-sensing (CS) theory. Here, the X-ray source moves along an arc within a limited scan angle (<= 180 degrees on a circular path set perpendicularly to the axial direction during the image acquisition. This geometry, compared to full angle (3601 scan geometry, allows imaging system to be designed more compactly and gives better tomographic quality than conventional linear digital tomosynthesis (DTS). We implemented an efficient CS based reconstruction algorithm for the proposed geomeny and performed systematic simulations to investigate the image characteristics. We successfully reconstructed CDTS images with incomplete projections acquired at several selected limited scan angles of 45 degrees, 90 degrees, 135 degrees, and 180 degrees for a given tomographic angle of 80 degrees and evaluated the reconstruction quality. Our simulation results indicate that the proposed method can provide superior tomographic quality for axial view and even for the other views (i.e., sagittal and coronal), as in computed tomography, to conventional DTS. (C) 2015 Elsevier B.v. All rights reserved,

关键词： Circular digital tomosynthesis Limited-scan angle Compressed-sensing

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Parallel multiframe blind deconvolution using wavelength diversity

Parallel multiframe blind deconvolution using wavelength div...

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conference on image reconstruction from incomplete data III

作者： Ingleby, HR McGaughey, DR Royal Mil Coll Canada Dept Elect & Comp Engn Kingston ON K7K 7B4 Canada

ISBN: (纸本)0819455008

The resolution of images captured through ground-based telescopes is generally limited by blurring effects due to atmospheric turbulence. We have developed a method to estimate both the original objects and the blurring function from a sequence of noisy blurred images, simultaneously collected at different wavelengths (wavelength diversity). The assumption of common path-length errors across the diversity channels allows for a parallel deconvolution procedure that exploits this coupling. In contrast with previous work, no a priori assumptions about the object's intensity distribution are required. The method is described, and preliminary results with real images collected with a bench-scale imaging system are presented, demonstrating the promise of the algorithm.

关键词： deconvolution wavelength diversity image restoration/reconstruction

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