Towards an efficient and robust foot classification from pedobarographic images

This paper presents a new computational framework for automatic foot classification from digital plantar pressure images. It classifies the foot as left or right and simultaneously calculates two well-known footprint indices: the Cavanagh's arch index (AI) and the modified AI. The accuracy of the framework was evaluated using a set of plantar pressure images from two common pedobarographic devices. The results were outstanding, as all feet under analysis were correctly classified as left or right and no significant differences were observed between the footprint indices calculated using the computational solution and the traditional manual method. The robustness of the proposed framework to arbitrary foot orientations and to the acquisition device was also tested and confirmed.     

生物组织背向SHG和TPEF的影响因素

由于生物组织的复杂性和多样性,以及样品制备等因素的影响,实验观察到的生物组织的背向二次谐波(second harmonic generation,SHG)和双光子激发荧光(two-photon excitation fluorescence,TPEF)效应的差异较大。以鼠尾组织作为实验对象,共40个切片,分为横向和纵向、HE染色和未染色四组,采用飞秒激光器作为激发光,用双光子激光扫描共焦显微镜(two-photon laser scanning confocal microscope,TPLSCM)观察和分析了样品在不同的制备方式、激发波长、激发功率、扫描深度等条件下的背向SHG和TPEF的变化曲线,讨论和比较了生物组织的背向SHG和TPEF的影响因素以及二者之间的异同,并尝试对实验现象做出了一定的解释。     

A Bayesian method for classification of images from electron micrographs

Particle classification is an important component of multivariate statistical analysis methods that has been used extensively to extract information from electron micrographs of single particles. Here we describe a new Bayesian Gibbs sampling algorithm for the classification of such images. This algorithm, which is applied after dimension reduction by correspondence analysis or by principal components analysis, dynamically learns the parameters of the multivariate Gaussian distributions that characterize each class. These distributions describe tilted ellipsoidal clusters that adaptively adjust shape to capture differences in the variances of factors and the correlations of factors within classes. A novel Bayesian procedure to objectively select factors for inclusion in the classification models is a component of this procedure. A comparison of this algorithm with hierarchical ascendant classification of simulated data sets shows improved classification over a broad range of signal-to-noise ratios.     

Quantitative imaging of fibrotic and morphological changes in liver of non-alcoholic steatohepatitis (NASH) model mice by second harmonic generation (SHG) and auto-fluorescence (AF) imaging using two-photon excitation microscopy (TPEM)

Non-alcoholic steatohepatitis (NASH) is a common liver disorder caused by fatty liver. Because NASH is associated with fibrotic and morphological changes in liver tissue, a direct imaging technique is required for accurate staging of liver tissue. For this purpose, in this study we took advantage of two label-free optical imaging techniques, second harmonic generation (SHG) and auto-fluorescence (AF), using two-photon excitation microscopy (TPEM). Three-dimensional ex vivo imaging of tissues from NASH model mice, followed by image processing, revealed that SHG and AF are sufficient to quantitatively characterize the hepatic capsule at an early stage and parenchymal morphologies associated with liver disease progression, respectively.     

A genetic classification of potato cultivars based on allozyme patterns

Summary A total of 25 potato isozymes were characterized by the numbers and relative mobilities of their allozymes, the subunit number, the subcellular localization, and the patterns of tissue expression. Using hierarchically ordered phenotype arrays at 9 of these isozymes, we were able to construct a dichotomous classification table for a total of 74 potato varieties, including those of most agronomical interest in Europe and North America.     

RegStatGel: proteomic software for identifying differentially expressed proteins based on 2D gel images

Image analysis of two-dimensional gel electrophoresis is a key step in proteomic workflow for identifying proteins that change under different experimental conditions. Since there are usually large amount of proteins and variations shown in the gel images, the use of software for analysis of 2D gel images is inevitable. We developed open-source software with graphical user interface for differential analysis of 2D gel images. The user-friendly software, RegStatGel, contains fully automated as well as interactive procedures. It was developed and has been tested under Matlab 7.01. AVAILABILITY: The database is available for free at http://www.mediafire.com/FengLi/2DGelsoftware.     

Automated detection and classification of high frequency oscillations (HFOs) in human intracereberal EEG

Discrete high-frequency oscillations (HFOs) in the range of 80–500 Hz have previously been recorded from human epileptic brains using intracereberal EEG and seem to be a reliable biomarker of seizure onset zone in patients with intractable epilepsy. Visual marking of HFOs bursts is tedious, highly time-consuming particularly for analyzing long-term multichannel EEG recordings, inevitably subjective and can be error prone. Thus, the development of automatic, fast and robust detectors is necessary and crucial for HFOs investigation and for propelling their eventual clinical applications. This paper presents a proposed algorithm for detection and classification of HFOs, which is a combination of both smoothed Hilbert Huang Transform (HHT) and root mean square (RMS) feature. Performance evaluation in terms of sensitivity and false discovery rate (FDR) were respectively 90.72% and 8.23% related to process validation. Indeed, the proposed method was efficient in terms of high sensitivity in which the majority of HFOs visually identified by experienced reviewers was correctly detected, and had a lower FDR. This would mean that only a low rate of detected events was misclassified as candidate HFOs events. The presented software is extremely fast, suitable and can be considered a valuable clinical tool for HFOs investigation.     

Analysis and classification of vegetation based on family composition

Summary The distributions of 54 plant families in 105 samples were studied to determine their indicator value in the vegetation of the Pacific Northwest. Families may be characteristic of particular environments or geographic conditions or they may distinguish between sets of samples. Principal components analysis, numerical classification, and stepwise discriminant analysis were used in this study.Principal components analysis identifies a family if it is common or dominant and has a distribution concentrated at one extreme of an axis of variation. Families with consistent patterns of distribution are useful in distinguishing between groups of samples previously created by numerical classification methods.Twenty-three families that contain environmental, successional, or geographical information were identified according to one or more methods.Nomenclature for species names in Washington follows Hitchcock & Cronquist (1973). Species names from the Alsek River, Yukon Territory, follows authorities cited by Douglas (1974).This study was funded in part by the U.S. National Science Foundation and by the Graduate School, University of Washington. We thank A.R. Kruckeberg, M.J. Cushman, R.A. Lerner, V. Seymour and A.F. Watson for thoughtful comments and stimulating discussion and R.W. Fonda, R.T. Kuromoto, G.W. Douglas and J.A. Belsky for the use of their data.     

Three-dimensional reconstruction and characterization of human external shapes from two-dimensional images using volumetric methods

This work presents a volumetric approach to reconstruct and characterise 3D models of external anatomical structures from 2D images. Volumetric methods represent the final volume using a finite set of 3D geometric primitives, usually designed as voxels. Thus, from an image sequence acquired around the object to reconstruct, the images are calibrated and the 3D models of the referred object are built using different approaches of volumetric methods. The final goal is to analyse the accuracy of the obtained models when modifying some of the parameters of the considered volumetric methods, such as the type of voxel projection (rectangular or accurate), the way the consistency of the voxels is tested (only silhouettes or silhouettes and photo-consistency) and the initial size of the reconstructed volume.     

Parallel morphological/neural processing of hyperspectral images using heterogeneous and homogeneous platforms

The wealth spatial and spectral information available from last-generation Earth observation instruments has introduced extremely high computational requirements in many applications. Most currently available parallel techniques treat remotely sensed data not as images, but as unordered listings of spectral measurements with no spatial arrangement. In thematic classification applications, however, the integration of spatial and spectral information can be greatly beneficial. Although such integrated approaches can be efficiently mapped in homogeneous commodity clusters, low-cost heterogeneous networks of computers (HNOCs) have soon become a standard tool of choice for dealing with the massive amount of image data produced by Earth observation missions. In this paper, we develop a new morphological/neural algorithm for parallel classification of high-dimensional (hyperspectral) remotely sensed image data sets. The algorithm’s accuracy and parallel performance is tested in a variety of homogeneous and heterogeneous computing platforms, using two networks of workstations distributed among different locations, and also a massively parallel Beowulf cluster at NASA’s Goddard Space Flight Center in Maryland.

Towards radiological diagnosis of abdominal adhesions based on motion signatures derived from sequences of cine-MRI images

This paper reports novel development and preliminary application of an image registration technique for diagnosis of abdominal adhesions imaged with cine-MRI (cMRI). Adhesions can severely compromise the movement and physiological function of the abdominal contents, and their presence is difficult to detect. The image registration approach presented here is designed to expose anomalies in movement of the abdominal organs, providing a movement signature that is indicative of underlying structural abnormalities. Validation of the technique was performed using structurally based in vitro and in silico models, supported with Receiver Operating Characteristic (ROC) methods. For the more challenging cases presented to the small cohort of 4 observers, the AUC (area under curve) improved from a mean value of 0.67 ± 0.02 (without image registration assistance) to a value of 0.87 ± 0.02 when image registration support was included. Also, in these cases, a reduction in time to diagnosis was observed, decreasing by between 20% and 50%. These results provided sufficient confidence to apply the image registration diagnostic protocol to sample magnetic resonance imaging data from healthy volunteers as well as a patient suffering from encapsulating peritoneal sclerosis (an extreme form of adhesions) where immobilization of the gut by cocooning of the small bowel is observed. The results as a whole support the hypothesis that movement analysis using image registration offers a possible method for detecting underlying structural anomalies and encourages further investigation.     

Recording,processing and analysis of grass root images from a rhizotron

To develop and test a system for computer-assisted image analysis, repeated video recordings of reed canary-grass roots (Phalaris arundinacea L.) were made in an 18-window rhizotron. The images were digitized and processed using a Unix computer and the Khoros software development environment.Two image sizes, 126×95 mm and 61×46 mm, both comprising 650 × 490 pixels, were compared. Among image processing techniques used were median filtering, segmentation and skeletonization. Root area and length in both the topsoil and subsoil were estimated using the two image sizes. The resolution (image size) strongly affected the calculated root lengths. The results were compared with root length measurements obtained manually.Statistically significant differences in root length and area in the topsoil were detected between the sampling dates using the computer-assisted methods. Possible sources of error and methods for reducing them are discussed.     

In vitro reconstruction of full thickness human skin on a composite collagen material

Rapid progress of in vitro techniques in the lastyears enabled the creation of organotypic skin cultures offering newpossibilities in wound treatment. Rebuilding of graft is one of the keyelementsof successful outcome of the procedure.In search for the best scaffold for organotypic skin culture, the novelcomposite xenogenic collagen based material with unique properties has beencreated and used to reconstitute full thickness human skin invitro. Based on our long established technology used for theproduction of collagen dressings for the treatment of burns, this novel,composite material offers excellent growth support of highly biodegradablespongy layer, combined with mechanical strength of collagen membrane. Themodulation of collagen properties was accomplished by consecutive treatmentwithhigh temperature and gamma irradiation. The use of the substrate enabled toobtain organotypic culture that resembles full thickness skin with fibroblastslayer and well-developed multilayer epithelium. Our new material offers easyhandling of obtained graft during surgery along with accelerated cell growth andcontrolled biodegradation of the culture support.     

Suitability of antral follicle counts and computer-assisted analysis of ultrasonographic and magnetic resonance images for estimating follicular reserve in porcine,ovine and bovine ovaries ex situ

This study was conducted to determine if correlations exist between the numbers of microscopic follicles comprising ovarian follicular reserve (OFR) and antral follicle counts (AFCs), and to assess the usefulness of computerized analyses of ovarian ultrasonograms and magnetic resonance (MR) images for estimating OFR in excised porcine, ovine and bovine ovaries. As a pre-requisite to these analyses, we characterized and compared ovarian cortical histomorhpology and follicle populations in the three species varying in prolificacy and overall reproductive longevity, and hence the total number of microscopic and antral follicles. Ultrasonographic and MR images were obtained at the scanner settings optimized to provide opposing contrasts between antral follicles and the ovarian stroma. Commercially available ImageProPlus® analytical software was used to calculate numerical pixel values (NPVs) and pixel heterogeneity (standard deviation of the pixel values) along the computer-generated lines (4–6) placed in the area corresponding to the ovarian cortex. The numbers of primordial (r = 0.38, P < 0.01) and intermediate follicles (r = 0.37, P < 0.01) were correlated with the numbers of antral follicles in bovine ovarian sections. The numbers of primordial (r = 0.28, P < 0.05), intermediate (r = 0.31, P < 0.01) and primary follicles (r = 0.27, P < 0.05) correlated directly with mean NPVs of the ultrasonographic ovarian images in cattle. There was a negative correlation between primary follicle numbers and NPVs of MR images (3D FAST-SPOILED GRADIENT ECHO) of the porcine ovarian cortex (r = −0.31, P < 0.05). To summarize, the numbers of primordial and intermediate follicles could only be estimated from AFCs in cows. Using ultrasound NPVs, the numbers of primordial, intermediate and primary follicles could be directly estimated in bovine ovaries and the quantitative image attributes of MR images were useful for quantifying porcine primary follicles. The bovine ovarian model is compatible with human situation and hence future studies should be undertaken to ascertain the usefulness of AFCs and ultrasonographic image analyses for estimating OFR in women.     

Deconvolution of images from 3D printed cells in layers on a chip

Layer‐by‐layer cell printing is useful in mimicking layered tissue structures inside the human body and has great potential for being a promising tool in the field of tissue engineering, regenerative medicine, and drug discovery. However, imaging human cells cultured in multiple hydrogel layers in 3D‐printed tissue constructs is challenging as the cells are not in a single focal plane. Although confocal microscopy could be a potential solution for this issue, it compromises the throughput which is a key factor in rapidly screening drug efficacy and toxicity in pharmaceutical industries. With epifluorescence microscopy, the throughput can be maintained at a cost of blurred cell images from printed tissue constructs. To rapidly acquire in‐focus cell images from bioprinted tissues using an epifluorescence microscope, we created two layers of Hep3B human hepatoma cells by printing green and red fluorescently labeled Hep3B cells encapsulated in two alginate layers in a microwell chip. In‐focus fluorescent cell images were obtained in high throughput using an automated epifluorescence microscopy coupled with image analysis algorithms, including three deconvolution methods in combination with three kernel estimation methods, generating a total of nine deconvolution paths. As a result, a combination of Inter‐Level Intra‐Level Deconvolution (ILILD) algorithm and Richardson‐Lucy (RL) kernel estimation proved to be highly useful in bringing out‐of‐focus cell images into focus, thus rapidly yielding more sensitive and accurate fluorescence reading from the cells in different layers. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:445–454, 2018     

Studies on the activation energy and deuterium isotope effect of human skin collagenase on homologous collagen substrates

The activation energy (EA) and solvent-deuterium kinetic isotope effect (kH/kD) of human skin fibroblast collagenase were studied on the homologous human type I, II, and III collagens in both native and denatured states. Values for EA on human type I and II collagens in solution were 47,000 and 61,000 cal, respectively. The Arrhenius plot for type III collagen, unlike that for the other types, was characterized by a break in EA at approximately 26 degrees C. At temperatures below this point, EA was 42,500 cal; at higher temperatures, EA fell to 29,500 cal. This latter value, intermediate between type I collagen monomers and denatured random gelatin alpha chains, appears to result from a further opening in the already loosened helix of the type III collagen molecule in the region of the 3/4:1/4 collagenase cleavage site. The EA of trypsin on native human type III collagen was also measured and found to be 70,000 cal. This high value calls into question the role of serine proteases in the physiologic degradation of this substrate; a much higher energy expenditure was required for trypsin to cleave type III collagen than for the fibroblast collagenase. Reaction velocity on human collagen types I-III in solution was slowed 15-35% (kH/kD = 1.2-1.5) by the substitution of deuterium for hydrogen in the solvent buffer. This value was far lower than that observed following the aggregation of solution monomers into insoluble fibrils (kH/kD = 9). Denaturation of triple helical monomers into random gelatin alpha chains eliminated any slowing by deuterium, and kH/kD was 1.0 in all cases. Since the same peptide bond hydrolysis accompanies the cleavage of all these forms of the collagen substrate, it would appear that the role of water at the rate-limiting step of collagen degradation may not reside in the hydrolysis of a peptide bond per se, but rather may reflect the difficulty in transporting water molecules to the site of such catalysis, especially following fibril aggregation.     

Comparison of collagen and glycosaminoglycan synthesis in attaching control and diabetic human skin fibroblasts

Summary Cultured fibroblasts derived from normal subjects and juvenile diabetics attach in the absence of serum to plastic culture dishes and secrete macromolecules, including collagenous components, hyaluronic acid, and proteoglycans into the medium and onto the plastic surface where they form a microexudate carpet. Most diabetic fibroblasts examined did not spread as well as normal cells during a 4-hr interval after the initial attachment. There were no significant differences between normal and diabetic cells with respect to proline and lysine incorporation and lysine hydroxylation. The percentage glycosylation of hydroxylysine was marginally higher in the media proteins of diabetic cells, but glycosylation in both normal and diabetic cells was elevated over that typically observed in human skin collagen. Collagenous components were estimated to constitute approximately 15–20% of the microexudate carpet fraction in both normal and diabetic cell strains. Diabetic fibroblasts exhibited a marginally lower ratio of heparan sulfate to chondroitin sulfate in the cell surface to matrix microexudate carpet fraction (trypsinate) than did normal fibroblasts. The hyaluronate and chondroitin sulfate contents of this fraction of diabetic cells were not significantly different from those of normal cells. This work was supported by Grants AM 11821 and AM 19606 from the National Institutes of Health, United States Public Health Service, by a grant from the American Diabetes Association (Leon W. Cunningham, Principal Investigator) and by the Vanderbilt Diabetes Endocrinology Center grant, AM 17026. R. E. Branson was the recipient of a research fellowship of the Juvenile Diabetes Foundation and of a National Institutes of Health Postdoctoral Fellowship AM 05636.