A New Rapid On-Line Imaging Method to Determine Particle Size Distribution of Granules

The purpose of this research was to study the feasibility of the new image analysis method in the particle size determination of the granules. The method is capable of forming a three-dimensional topographic image of a sample surface from a digital picture. In the method, a flat granule bed surface was illuminated from three different directions, using the three primary colors (red, green, and blue). One color picture was taken by a digital camera, after which a topographic image of the object surface was constructed. The particle size distribution was then calculated from the image data. The particle size analysis method was tested both off-line and on-line. Off-line particle size measurement results determined by the image analysis method corresponded quite well to those of sieve analysis in the size fraction range 250–1,000 μm. In on-line application, images were successfully retrieved and median granule size trend could be calculated and followed during fluid bed granulations.     

A novel in situ atomic force microscopy imaging technique to probe surface morphological features of starch granules

The application of atomic force microscopy (AFM) for observing iodine complexes in starch has been limited due to limitations including granular sample fixation techniques and possible unintended reactions with embedding materials such as epoxy resins or adhesives. In this paper, a new method is described that employs an optical microscopic technique to ensure that the tip of the AFM is scanning a specified granule without any probe-induced particle movement by the AFM probe motion. The direct sprinkling of samples on a two-sided adhesive tape allows investigations in an in situ environment of the un-embedded starch granule surface and thus provides high-resolution images of granule morphology and phase changes of starches in the presence of humidity and with iodine vapor. These observations demonstrate that this novel in situ AFM imaging technique allows us to visualize the hair-like structures on the surface of granular starches when starches are exposed to iodine vapor under humid environments. This study reveals that the hair-like extensions on the starch granule surfaces are strongly dependent on the organization of the glucan polymers within corn or potato starch.     

Cryo-electron microscope image denoising based on the geodesic distance

Background

To perform a three-dimensional (3-D) reconstruction of electron cryomicroscopy (cryo-EM) images of viruses, it is necessary to determine the similarity of image blocks of the two-dimensional (2-D) projections of the virus. The projections containing high resolution information are typically very noisy. Instead of the traditional Euler metric, this paper proposes a new method, based on the geodesic metric, to measure the similarity of blocks.

Results

Our method is a 2-D image denoising approach. A data set of 2243 cytoplasmic polyhedrosis virus (CPV) capsid particle images in different orientations was used to test the proposed method. Relative to Block-matching and three-dimensional filtering (BM3D), Stein’s unbiased risk estimator (SURE), Bayes shrink and K-means singular value decomposition (K-SVD), the experimental results show that the proposed method can achieve a peak signal-to-noise ratio (PSNR) of 45.65. The method can remove the noise from the cryo-EM image and improve the accuracy of particle picking.

Conclusions

The main contribution of the proposed model is to apply the geodesic distance to measure the similarity of image blocks. We conclude that manifold learning methods can effectively eliminate the noise of the cryo-EM image and improve the accuracy of particle picking.

     

Digital holography-based 3D particle localization for single-molecule tweezer techniques

We present a three-dimensional (3D) imaging technique for the fast tracking of microscopic objects in a fluid environment. Our technique couples digital holographic microscopy with three-dimensional localization via parabolic masking. Compared with existing approaches, our method reconstructs 3D volumes from single-plane images, which greatly simplifies image acquisition, reduces the demand on microscope hardware, and facilitates tracking higher densities of microscopic particles while maintaining similar levels of precision. We demonstrate utility of this method in magnetic tweezer experiments, opening their use to multiplexed single-molecule force spectroscopy assays, which were previously limited by particle crowding and fast dissociation times. We propose that our technique will also be useful in other applications that involve the tracking of microscopic objects in three dimensions, such as studies of microorganism motility and 3D flow characterization of microfluidic devices.     

A method to estimate in vivo dynamic articular surface interaction

This paper describes a method to calculate and visualize the proximity of subchondral bone surfaces during dynamic movement. This method combines high-speed biplane radiographic image data and three-dimensional (3D) bone surface information derived from computed tomography to determine subchondral bone motion during dynamic activities. Knowledge of in vivo subchondral bone motion may be useful in the study of osteoarthritis, in biomechanical modeling, and in identifying normal and pathological joint mechanics. This method can be used to identify the regions of close contact during dynamic motion, to calculate the surface area of subchondral bone within close contact, and to determine the changing position of the close contact area during dynamic activities. None of this informations can be obtained using other currently available 3D motion analysis techniques. Example applications showing dynamic in vivo tibio-femoral bone surface motion during canine gait and human one-legged hopping are presented.     

Single particle 3D reconstruction for 2D crystal images of membrane proteins

In cases where ultra-flat cryo-preparations of well-ordered two-dimensional (2D) crystals are available, electron crystallography is a powerful method for the determination of the high-resolution structures of membrane and soluble proteins. However, crystal unbending and Fourier-filtering methods in electron crystallography three-dimensional (3D) image processing are generally limited in their performance for 2D crystals that are badly ordered or non-flat. Here we present a single particle image processing approach, which is implemented as an extension of the 2D crystallographic pipeline realized in the 2dx software package, for the determination of high-resolution 3D structures of membrane proteins. The algorithm presented, addresses the low single-to-noise ratio (SNR) of 2D crystal images by exploiting neighborhood correlation between adjacent proteins in the 2D crystal. Compared with conventional single particle processing for randomly oriented particles, the computational costs are greatly reduced due to the crystal-induced limited search space, which allows a much finer search space compared to classical single particle processing. To reduce the considerable computational costs, our software features a hybrid parallelization scheme for multi-CPU clusters and computer with high-end graphic processing units (GPUs). We successfully apply the new refinement method to the structure of the potassium channel MloK1. The calculated 3D reconstruction shows more structural details and contains less noise than the map obtained by conventional Fourier-filtering based processing of the same 2D crystal images.     

TMaCS: A hybrid template matching and classification system for partially-automated particle selection

Selection of particle images from electron micrographs presents a bottleneck in determining the structures of macromolecular assemblies by single particle electron cryomicroscopy (cryo-EM). The problem is particularly important when an experimentalist wants to improve the resolution of a 3D map by increasing by tens or hundreds of thousands of images the size of the dataset used for calculating the map. Although several existing methods for automatic particle image selection work well for large protein complexes that produce high-contrast images, it is well known in the cryo-EM community that small complexes that give low-contrast images are often refractory to existing automated particle image selection schemes. Here we develop a method for partially-automated particle image selection when an initial 3D map of the protein under investigation is already available. Candidate particle images are selected from micrographs by template matching with template images derived from projections of the existing 3D map. The candidate particle images are then used to train a support vector machine, which classifies the candidates as particle images or non-particle images. In a final step in the analysis, the selected particle images are subjected to projection matching against the initial 3D map, with the correlation coefficient between the particle image and the best matching map projection used to assess the reliability of the particle image. We show that this approach is able to rapidly select particle images from micrographs of a rotary ATPase, a type of membrane protein complex involved in many aspects of biology.     

Perspectives in three-dimensional analysis of bone samples using synchrotron radiation microtomography.

In this paper we present a methodology based on 3D synchrotron radiation microtomography to analyze non-destructively 3D bone samples. After a technical presentation of the imaging system and the image analysis techniques, we report results on three-dimensional analysis of vertebral samples from women of different ages. The new capabilities of this technique for the investigation of bone are discussed. They include a high spatial resolution down to the micron level, a high density resolution allowing a local quantification of bone mineralization, phase contrast imaging and advances in 3D image analysis.     

Inference of Euler angles for single-particle analysis by means of evolutionary algorithms

Single-particle analysis is one of the methods for structural studies of protein and macromolecules; it requires advanced image analysis of electron micrographics. Reconstructing three-dimensional (3D) structure from microscope images is not an easy analysis because of the low image resolution of images and lack of the directional information of images in 3D structure. To improve the resolution, different projections are aligned, classified, and averaged. Inferring the orientations of these images is so difficult that the task of reconstructing 3D structures depends upon the experience of researchers. But recently, a method to reconstruct 3D structures was automatically devised. In this paper, we propose a new method for determining Euler angles of projections by applying genetic algorithms. We empirically show that the proposed approach has improved the previous one in terms of computational time and acquired precision.     

Binding, reconstitution and 2D crystallization of membrane or soluble proteins onto functionalized lipid layer observed in situ by reflected light microscopy

Monolayer of functionalized lipid spread at the air/water interface is used for the structural analysis of soluble and membrane proteins by electron crystallography and single particle analysis. This powerful approach lacks of a method for the screening of the binding of proteins to the surface of the lipid layer. Here, we described an optical method based on the use of reflected light microscopy to image, without the use of any labeling, the lipid layer at the surface of buffers in the Teflon wells used for 2D crystallization. Images revealed that the lipid layer was made of a monolayer coexisting with liposomes or aggregates of lipids floating at the surface. Protein binding led to an increase of the contrast and the decrease of the fluidity of the lipid surface, as demonstrated with the binding of soluble Shiga toxin B subunit, of purple membrane and of solubilized His-BmrA, a bacterial ABC transporter. Moreover the reconstitution of membrane proteins bound to the lipidic surface upon detergent removal can be followed through the appearance of large recognizable domains at the surface. Proteins binding and reconstitution were further confirmed by electron microcopy. Overall, this method provides a quick evaluation of the monolayer trials, a significant reduction in screening by transmission electron microscopy and new insights in the proteins binding and 2D crystallogenesis at the lipid surface.     

RV functional imaging: 3-D echo-derived dynamic geometry and flow field simulations

We describe a novel functional imaging approach for quantitative analysis of right ventricular (RV) blood flow patterns in specific experimental animals (or humans) using real-time, three-dimensional (3-D) echocardiography (RT3D). The method is independent of the digital imaging modality used. It comprises three parts. First, a semiautomated segmentation aided by intraluminal contrast medium locates the RV endocardial surface. Second, a geometric scheme for dynamic RV chamber reconstruction applies a time interpolation procedure to the RT3D data to quantify wall geometry and motion at 400 Hz. A volumetric prism method validated the dynamic geometric reconstruction against simultaneous sonomicrometric canine measurements. Finally, the RV endocardial border motion information is used for mesh generation on a computational fluid dynamics solver to simulate development of the early RV diastolic inflow field. Boundary conditions (tessellated endocardial surface nodal velocities) for the solver are directly derived from the endocardial geometry and motion information. The new functional imaging approach may yield important kinematic information on the distribution of instantaneous velocities in the RV diastolic flow field of specific normal or diseased hearts.     

Unifying shading and texture through an active observer

Shading (variations of image intensity) provides an important cue for understanding the shape of three-dimensional surfaces from monocular views. On the other hand, texture (distribution of discontinuities on the surface) is a strong cue for recovering surface orientation by using monocular images. But given the image of an object or scene, what technique should we use to recover the shape of what is image? Resolution of shape from shading requires knowledge of the reflectance of the imaged surface and, usually, the fact that it is smooth (i.e. it shows no discontinuities). Determination of shape from texture requires knowledge of the distribution of surface markings (i.e. discontinuities). One might expect that one method would work when the other does not. I present a theory on how an active observer can determine shape from the image of an object or scene regardless of whether the image is shaded, textured, or both, and without any knowledge of reflectance maps or the distribution of surface markings. The approach is successful because the active observer is able to manipulate the constraints behind the perceptual phenomenon at hand and thus derive a simple solution. Several experimental results are presented with real and synthetic images.     

A new method to measure cortical growth in the developing brain

Folding of the cerebral cortex is a critical phase of brain development in higher mammals but the biomechanics of folding remain incompletely understood. During folding, the growth of the cortical surface is heterogeneous and anisotropic. We developed and applied a new technique to measure spatial and directional variations in surface growth from longitudinal magnetic resonance imaging (MRI) studies of a single animal or human subject. MRI provides high resolution 3D image volumes of the brain at different stages of development. Surface representations of the cerebral cortex are obtained by segmentation of these volumes. Estimation of local surface growth between two times requires establishment of a point-to-point correspondence ("registration") between surfaces measured at those times. Here we present a novel approach for the registration of two surfaces in which an energy function is minimized by solving a partial differential equation on a spherical surface. The energy function includes a strain-energy term due to distortion and an "error energy" term due to mismatch between surface features. This algorithm, implemented with the finite element method, brings surface features into approximate alignment while minimizing deformation in regions without explicit matching criteria. The method was validated by application to three simulated test cases and applied to characterize growth of the ferret cortex during folding. Cortical surfaces were created from MRI data acquired in vivo at 14 days, 21 days, and 28 days of life. Deformation gradient and Lagrangian strain tensors describe the kinematics of growth over this interval. These quantitative results illuminate the spatial, temporal, and directional patterns of growth during cortical folding.     

The combination of photogrammetry and finite elements for a fine grained functional analysis of anatomical structures

Summary A new method of functional morphological analysis is presented. Combining stereophotogrammetry with the finite element technique, a new approach, permits a three-dimensional numerical stress analysis of arbitrarily shaped bodies to be performed. The stereophotogrammetric method which originated for three-dimensional calculations in the study of surfaces in land surveying is well suited for the determination of the nodal co-ordinates required for the finite element method, an engineering technique developed for behavioural analysis of solids and fluids responding to external forces. This approach was tested in a study of the functional morphology of the bill of an African wading bird, the shoebill Balaeniceps rex. A few findings of that study are given here in order to demonstrate the method. Advantages of the finite element method compared with other techniques for stress analysis of anatomical structures are also discussed. The method presents exciting possibilities for predicting displacement and stress responses more accurately and in much greater detail. The scope of this powerful computerized stress analysis technique is greatly enhanced with the introduction of stereophotogrammetry for determining the three-dimensional co-ordinates of complex anatomical structures. With the finite element method, the properties of the bone structure can be modelled as they occur in the life of the animal. This is not possible with physical models. Furthermore, rare specimens can be analysed non-destructively.     

Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space

To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured.     

High Resolution,Large Deformation 3D Traction Force Microscopy

Traction Force Microscopy (TFM) is a powerful approach for quantifying cell-material interactions that over the last two decades has contributed significantly to our understanding of cellular mechanosensing and mechanotransduction. In addition, recent advances in three-dimensional (3D) imaging and traction force analysis (3D TFM) have highlighted the significance of the third dimension in influencing various cellular processes. Yet irrespective of dimensionality, almost all TFM approaches have relied on a linear elastic theory framework to calculate cell surface tractions. Here we present a new high resolution 3D TFM algorithm which utilizes a large deformation formulation to quantify cellular displacement fields with unprecedented resolution. The results feature some of the first experimental evidence that cells are indeed capable of exerting large material deformations, which require the formulation of a new theoretical TFM framework to accurately calculate the traction forces. Based on our previous 3D TFM technique, we reformulate our approach to accurately account for large material deformation and quantitatively contrast and compare both linear and large deformation frameworks as a function of the applied cell deformation. Particular attention is paid in estimating the accuracy penalty associated with utilizing a traditional linear elastic approach in the presence of large deformation gradients.     

A fully automatic 3D reconstruction method using simulated annealing enables accurate posterioric angular assignment of protein projections

Single-particle analysis is a structure determining method using electron microscopic (EM) images, which does not require protein crystal. In this method, projections are picked up and used to reconstruct a three-dimensional (3D) structure. When the conical tilting method is not available, the particle images are usually classified and averaged to improve the signal-to-noise ratio. The Euler angles of these average images must be posteriorically assigned to create a primary 3D model. We developed a new, fully automatic unsupervised Euler angle assignment method, which does not require an initial 3D reference and which is applicable to asymmetric molecules. In this method, the Euler angle of each average image is initially set randomly and then automatically corrected in relation to those of the other averages by iterated optimizations using the Simulated Annealing (SA) algorithm. At each iteration, the 3D structure is reconstructed based on the current Euler angles and reprojected back in the average-input directions. A modified cross-correlation between each reprojection and its corresponding original average is then calculated. The correlations are summed as a total 3D echo-correlation score to evaluate the Euler angles at this iteration. Then, one of the projections is selected, its Euler angle is changed randomly, and the score is also calculated. Based on the score change, judgment of whether to accept or reject the new angle is made using the SA algorithm, which is introduced to overcome the local minimums. After a certain number of iterations of this process, the angles of all averages converge so as to create a reliable primary 3D model. This echo-correlated 3D reconstruction with simulated annealing also has potential for wide application to general 3D reconstruction from various types of 2D images.