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Subcellular Composition Based On Light-Element EELS

Microscopy and Microanalysis 2020年第S2期3卷 927-928页

作者： R.D. Leapman Biomedical Engineering & Instrumentation Program NCRR National Institutes of Health Bethesda MD 20892.

Recent work on biological electron energy-loss spectroscopy (EELS) in the analytical electron microscope has focused on measuring concentrations of the important elements, calcium and phosphorus. Analysis of the light elements, for which EELS was originally thought to be best suited, has so far not yielded much useful information from biological specimens. Whereas low-loss fine structure has been analyzed successfully to measure distributions of water and protein in frozen-hydrated cells, core-edge fine structure cannot be recorded at sufficiently low dose to obtain useful chemical information. However, the atomic ratios of the light elements (carbon, nitrogen and oxygen) obtained from EELS are less dependent on electron dose. Together with sulfur (in proteins) and phosphorus (in nucleic acids, phospholipids and phosphates) these ratios can help determine the types and proportions of compounds that are present at the subcellular level. Here we re-examine the potential for making these kinds of measurements.

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Capabilities and Limitations of Biological Electron Energy-Loss Spectroscopy

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Microscopy and Microanalysis 2020年第S2期3卷 871-872页

作者： R.D. Leapman S.B. Andrews Biomedical Engineering & Instrumentation Program NCRR Bethesda MD 20892. Laboratory of Neurobiology NINDS National Institutes of HealthBethesda MD 20892.

Perhaps the ultimate aim of analytical electron microscopy in biology is to detect single atoms or ions bound to isolated macromolecular assemblies and small cellular organelles rapidly frozen in their native state. Although the meaningful spatial resolution in such analyses is limited to ∽10 nm or more by radiation damage, the high intrinsic sensitivity of electron energy-loss spectroscopy (EELS) coupled with recent developments seems to make this rather ambitious goal—originally proposed some twenty years ago—within reach. Here we describe examples where EELS has been able to detect surprisingly small numbers of atoms in biological specimens and discuss some fundamental limits that are encountered as well as some possible strategies for circumventing these *** our laboratory we have used a scanning transmission electron microscope (STEM) equipped with a field-emission source and parallel-detection EELS because the probe size and collection efficiency of this instrument are optimized to give the lowest detectable number of atoms and lowest detectable atomic fraction.

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Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI

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Journal of Magnetic Resonance 2011年第2期213卷 560-570页

作者： Basser, Peter J. Pierpaoli, Carlo Biomedical Engineering and Instrumentation Program NCRR Building 13 Room 3N17 13 South Drive BethesdaMD20892-5766 United States Neuroimaging Branch NINDS Building 13 Room 3N17 13 South Drive BethesdaMD20892-5766 United States

Quantitative-diffusion-tensor MRI consists of deriving and displaying parameters that resemble histological or physiological stains, i.e., that characterize intrinsic features of tissue microstructure and microdynamics. Specifically, these parameters are objective, and insensitive to the choice of laboratory coordinate system. Here, these two properties are used to derive intravoxel measures of diffusion isotropy and the degree of diffusion anisotropy, as well as intervoxel measures of structural similarity, and fiber-tract organization from the effective diffusion tensor, D, which is estimated in each voxel. First, D is decomposed into its isotropic and anisotropic parts, 〈D〉 I and D – 〈D〉 I, respectively (where 〈D〉 = Trace(D)/3 is the mean diffusivity, and I is the identity tensor). Then, the tensor (dot) product operator is used to generate a family of new rotationally and translationally invariant quantities. Finally, maps of these quantitative parameters are produced from high-resolution diffusion tensor images (in which D is estimated in each voxel from a series of 2D-FT spin-echo diffusion-weighted images) in living cat brain. Due to the high inherent sensitivity of these parameters to changes in tissue architecture (i.e., macromolecular, cellular, tissue, and organ structure) and in its physiologic state, their potential applications include monitoring structural changes in development, aging, and disease. © 2011

关键词： Tensors

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Pre-filtering for the initialization of multi-wavelet transforms

Pre-filtering for the initialization of multi-wavelet transf...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M.J. Vrhel A. Aldroubi Biomedical Engineering and Instrumentation Program NCRR Bldg National Institutes of Health DHHS Bethesda MD USA

We introduce a new method for initializing the multi-wavelet decomposition algorithm. The approach assumes that the input signal is contained within some well-defined subspace of L/sub 2/ (e.g. space of bandlimited functions). The initialization algorithm is the orthogonal projection of the input signal into the space defined by the multi-scaling function. Unlike an interpolation approach, the projection method will always have a solution. We provide examples and implementation details.

关键词： Interpolation Convolution biomedical engineering Instruments Algorithm design and analysis Compaction Signal generators Digital images Filtering Equations

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Wavelets, statistics, and biomedical applications

Wavelets, statistics, and biomedical applications

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IEEE Workshop on Statistical Signal and Array Processing

作者： M. Unser Biomedical Engineering and Instrumentation Program NCRR National Institutes of Health DHHS Bethesda MD USA

This paper emphasizes the statistical properties of the wavelet transform (WT) and discusses some examples of applications in medicine and biology. The redundant forms of the transform (continuous wavelet transform (CWT) and wavelet frames) are well suited for detection tasks (e.g., spikes in EEG, or microcalcifications in mammograms). The CWT, in particular, can be interpreted as a prewhitening multi-scale matched filter. Redundant wavelet decompositions are also very useful for the characterization of singularities, as well as for the time-frequency analysis of non-stationary signals. We discuss some examples of applications in phonocardiography, electrocardiography (EGG), and electroencephalography (EEG). Wavelet bases (WB) provide a similar, non-redundant decomposition of a signal in terms of the shifts and dilations of a wavelet. This makes WB well suited for any of the tasks for which block transforms have been used traditionally. Wavelets, however, may present certain advantages because they can improve the signal-to-noise ratio, while retaining a certain degree of localization in the time (or space) domain. We present three illustrative examples. The first is a denoising technique that applies a soft threshold in the wavelet domain. The second is a more refined version that uses generalized Wiener filtering. The third is a statistical method for detecting and locating patterns of brain activity in functional images acquired using magnetic resonance imaging (MRI). We conclude by describing a wavelet generalization of the classical Karhunen-Loeve transform.

关键词： Statistics Continuous wavelet transforms Wavelet transforms Electroencephalography Wavelet domain Magnetic resonance imaging biomedical imaging Matched filters Wavelet analysis Time frequency analysis

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CRYOELECTRON ENERGY-LOSS SPECTROSCOPY - OBSERVATIONS ON VITRIFIED HYDRATED SPECIMENS AND RADIATION-DAMAGE

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ULTRAMICROSCOPY 1995年第1-4期59卷 71-79页

作者： LEAPMAN, RD SUN, SQ Biomedical Engineering and Instrumentation Program NCRR National Institutes of Health Bethesda MD 20892 USA.

Valence electron energy loss spectroscopy (EELS) has been used to characterize the composition of frozen-hydrated specimens in the electron microscope. Fine structure in the energy range up to 30 eV provides a means of distinguishing between vitreous and crystalline ice. Some features of the ice spectrum can be understood in terms of transitions between molecular orbitals in the water molecule and by the existence of excitons in the solid. Spectra from hydrated biological specimens can be analyzed to obtain quantitative estimates of the water content by fitting contributions from the ice and organic components. EELS also provides information about the radiation chemistry that occurs when hydrated specimens are exposed to the electron beam. From the observation of the hydrogen K-edge at similar to 13 eV, it can be deduced that bubbles of molecular hydrogen are evolved during irradiation at doses of > 10(4) nm(-2), and that these bubbles contain gas at pressures in excess of one thousand atmospheres.

关键词： Animals Cryopreservation Cryopreservation Liver/radiation effects Mice Microscopy, Electron/methods Water

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Inferring microstructural features and the physiological state of tissues from diffusion-weighted images

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NMR IN BIOMEDICINE 1995年第7-8期8卷 333-344页

作者： Basser, PJ Biomedical Engineering and Instrumentation Program NCRR National Institutes of Health Building 13 Room 3N-17 13 South Drive Bethesda MD 20892-5766 USA

We review several methods that have been developed to infer microstructural and physiological information about isotropic and anisotropic tissues from diffusion weighted images (DWIs), These include Diffusion Imaging (DI), Diffusion Tensor Imaging (DTI), isotropically weighted imaging, and q-space imaging. Just as DI provides useful information about molecular displacements in one dimension with which to characterize diffusion in isotropic tissues, DTI provides information about molecular displacements in three dimensions needed to characterize diffusion Is anisotropic tissues. DTI also furnishes scalar parameters that behave like quantitative histological or physiological 'stains' for different features of diffusion, These include Trace(D), which is related to the mean diffusivity, and a family of parameters derived from the diffusion tensor, D, which characterize different features of anisotropic diffusion, Simple thought experiments and geometrical constructs, such as the diffusion ellipsoid, can be used to understand water diffusion in isotropic add anisotropic media, and the NMR experiments used to characterize it.

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Multigrid adaptive image processing

Multigrid adaptive image processing

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IEEE International Conference on Image Processing

作者： M. Unser Biomedical Engineering and Instrumentation Program NCRR Bethesda MD USA

We consider a general weighted least squares approximation problem with a membrane spline regularization term. The key parameters in this formulation are the weighting factors which provide the possibility of a spatial adaptation. We prove that the corresponding space-varying variational problem is well posed, and propose a novel multigrid computational solution. This multiresolution relaxation scheme uses three image pyramids (input data, weights, and current solution) and allows for a very efficient computation with an effective O(N) complexity, where N is the number of pixels. This general multigrid solver can be useful for a variety of image processing tasks. In particular, we propose new multigrid solutions for noise reduction in images (adaptive smoothing spline), interpolation/reconstruction of missing image data, and image segmentation using an adaptive extension of the K-means clustering algorithm.

关键词： Image processing Spline Least squares approximation Biomembranes Spatial resolution Image resolution Pixel Noise reduction Smoothing methods Interpolation

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Compositional Imaging with Electron Energy Loss Spectroscopy

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Microscopy and Microanalysis 1995年第3期1卷 93-108页

作者： Leapman, R.D. Biomedical Engineering and Instrumentation Program NCRR National Institutes of Health Bethesda. Maryland 20892 United States Department of Materials Science and Engineering Lehigh University Whitaker Laboratory Gatan Research and Development Pennsylvania 18015-3195 Pleasanton94588 #5 Bethlehem United States

: Compositional imaging with electron energy loss spectroscopy (EELS) can be performed in both the energy-filtering transmission electron microscope (EFTEM) and in the scanning transmission electron microscope (STEM). Quantitative elemental distributions are obtained from core-edges produced by inner-shell excitations, although more detailed information about chemical bonding and electronic structure is also available from the fine structure associated with valence electron excitations. The fixed-beam EFTEM can provide data from large numbers of pixels very rapidly and offers an advantage for analysis of extended specimen regions containing relatively high atomic concentrations. Acquisition of entire spectra at each pixel in the field-emission STEM (spectrum-imaging technique) provides improved flexibility and accuracy despite the longer recording times. Spectrum-imaging allows post facto data processing with parameters that can be varied after acquisition is completed. In suitably thin specimens, EELS compositional mapping can provide a sensitivity of a few atoms for certain elements. © 1995, Cambridge University Press. All rights reserved.

关键词： compositional mapping electron energy loss spectroscopy microanalysis spectral processing spectrum-imaging STEM transmission electron microscope

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Affine transformations of images: A least squares formulation

Affine transformations of images: A least squares formulatio...

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The 1994 1st IEEE International Conference on Image Processing

作者： Unser, M. Neimark, M.A. Lee, C. Biomedical Engineering and Instrumentation Program NCRR National Institutes of Health Bldg. 13 Room 3W13 BethesdaMD20892 United States

We present a general framework for the design of discrete geometrical transformation operators, including rotations and scaling. The first step is to fit the discrete input image with a continuous model that provides an exact interpolation at the pixel locations. The corresponding image model is selected within a certain subspace V(φ)⊂L2(RP) that is generated from the integer translates of a generating function φ;particular examples of this construction include polynomial spline and bandlimited signal representations. Next, the geometrical transformation is applied to the fitted model, and the result is re-projected onto the representation space. This procedure yields a solution that is optimal in the least squares sense. We show that this method can be implemented exactly using a combination of digital filters and a re-sampling step that uses a modified sampling kernel. We then derive explicit implementation formulas for the piecewise constant and cubic spline image models. Finally, we consider image processing examples and show that the present method compares very favorably with a standard interpolation that uses the same model. © 1994 IEEE.

关键词： Interpolation

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