Comparison of methods for measuring soil microbial activity using cotton strips and a respirometer

In order to develop a method of measuring the level of microbial activity in soil that is suitable for use by farmers, land managers, and other non-scientists, a simple method for determining soil microbial activity was evaluated and compared with two standard techniques. Soils sampled from vegetable farms in south east Queensland were incubated in the laboratory under controlled moisture and temperature conditions. Three methods were used to measure soil microbial activity, a respirometry method and two methods using the cotton strip assay (CSA) technique (image analysis and tensometer). The standard CSA method measured loss of tensile strength over a 35 day incubation period of buried cotton strips using a tensometer. The new CSA technique measured the intensity of staining by microbes using a flatbed scanner to create an image of the cotton strip whose staining percentage was determined using Photoshop software. The respirometry method used the substrate induced respiration rate (SIR) to determine microbial biomass in the soil at day 12 of incubation. The strong correlation between the image analysis method and the tensometer method (r(2)=0.81), a technique used by scientific researchers, suggests that the image analysis method could be used to monitor aspects of soil biological health by general community land-care groups and farmers. The image analysis method uses equipment which is readily available and, while not strongly correlated with more precise measurements of soil biological activity such as microbial biomass (r(2)=0.26), it can detect gross trends in biological health in a soil monitoring program. The CSA method using image analysis was the cheapest technique to measure soil microbial activity. CSA using image analysis can be a valuable tool in conjunction with other simple indicators of soil physical and chemical health such as slaking and pH to monitor soil amelioration or rehabilitation programs.     

Comparison between Different Intensity Normalization Methods in 123I-Ioflupane Imaging for the Automatic Detection of Parkinsonism

Intensity normalization is an important pre-processing step in the study and analysis of DaTSCAN SPECT imaging. As most automatic supervised image segmentation and classification methods base their assumptions regarding the intensity distributions on a standardized intensity range, intensity normalization takes on a very significant role. In this work, a comparison between different novel intensity normalization methods is presented. These proposed methodologies are based on Gaussian Mixture Model (GMM) image filtering and mean-squared error (MSE) optimization. The GMM-based image filtering method is achieved according to a probability threshold that removes the clusters whose likelihood are negligible in the non-specific regions. The MSE optimization method consists of a linear transformation that is obtained by minimizing the MSE in the non-specific region between the intensity normalized image and the template. The proposed intensity normalization methods are compared to: i) a standard approach based on the specific-to-non-specific binding ratio that is widely used, and ii) a linear approach based on the α-stable distribution. This comparison is performed on a DaTSCAN image database comprising analysis and classification stages for the development of a computer aided diagnosis (CAD) system for Parkinsonian syndrome (PS) detection. In addition, these proposed methods correct spatially varying artifacts that modulate the intensity of the images. Finally, using the leave-one-out cross-validation technique over these two approaches, the system achieves results up to a 92.91% of accuracy, 94.64% of sensitivity and 92.65 % of specificity, outperforming previous approaches based on a standard and a linear approach, which are used as a reference. The use of advanced intensity normalization techniques, such as the GMM-based image filtering and the MSE optimization improves the diagnosis of PS.     

Topographic Factor Analysis: A Bayesian Model for Inferring Brain Networks from Neural Data

The neural patterns recorded during a neuroscientific experiment reflect complex interactions between many brain regions, each comprising millions of neurons. However, the measurements themselves are typically abstracted from that underlying structure. For example, functional magnetic resonance imaging (fMRI) datasets comprise a time series of three-dimensional images, where each voxel in an image (roughly) reflects the activity of the brain structure(s)–located at the corresponding point in space–at the time the image was collected. FMRI data often exhibit strong spatial correlations, whereby nearby voxels behave similarly over time as the underlying brain structure modulates its activity. Here we develop topographic factor analysis (TFA), a technique that exploits spatial correlations in fMRI data to recover the underlying structure that the images reflect. Specifically, TFA casts each brain image as a weighted sum of spatial functions. The parameters of those spatial functions, which may be learned by applying TFA to an fMRI dataset, reveal the locations and sizes of the brain structures activated while the data were collected, as well as the interactions between those structures.     

Trabecular bone densitometry using interactive image analysis

Interactive image analysis is a novel application of digital image processing to the densitometry of trabecular bone. Briefly, the exposed surfaces of bleached slices of bone are illuminated so that the trabecular tips are bright in relation to the interstices. The image is then captured by a TV camera and digitized with an interactive image analysis system. A grey scale is then chosen that differentiates the bone at the surface from the background. Finally, a computer program calculates the area fraction of bone within a user-specified box which, by Delesse's principle, is an estimate of the volume fraction of bone. The reproducibility of the technique (expressed as an average sd) is ± 1.5 vol. % and has surface-discriminating capabilities comparable to the traditional point-counting method but is faster and more precise. Most importantly, the technique permits biomechanical testing of the sample after its density has been determined.     

A program system for interactive measurements on digitized cell images.

Using a high precision image scanner and a PDP-8/F minicomputer, we have developed a program system for interactive measurements on microscopic images. By giving simple keyboard commands, the operator can run the image scanner and manipulate the digitized images. The interface between the operator and the microscope-computer system is a Tektronix 4010 graphic terminal. The system allows objects to be isolated and parameters to be calculated from each object, e.g., parameters characterizing shape of the object, irregularity in light transmission over the object, area, integrated light transmission, etc. Objects are isolated and parameters are calculated under complete operator control using interactive computer graphics technique. Calculated parameters may be stored in dedicated data records, which are stored in files for later statistical analysis. The system also includes a statistical evaluation part. Technically, the system consists of a command scanner, which translates commands into internal representation, a parser, which checks the syntax of the commands, and an interpreter, which executes the commands. The system is designed so that new commands can be added easily.     

Image Analysis of the Growth of Globodera pallida and Meloidogyne incognita on Transgenic Tomato Roots Expressing Cystatins

An approach based on image analysis that enables rapid collection and analysis of nematode size and shape during growth is reported. This technique has been applied to assess Meloidogyne incognita and Globodera pallida during their development over 35 and 42 days, respectively, on transgenic tomato roots expressing the wild-type rice cystatin Oc-I or an engineered variant, Oc-IAD86. Morphometric values were established that subdivided enlarged saccate females from other life stages. Analysis of this data subset indicates that the size of females and the frequency with which they parasitize roots expressing a cystatin are reduced. Results also demonstrate that cystatins can influence the growth of G. pallida prior to the adult stage. Similar image analysis procedures should be generally applicable to the study of host status or erivironmental factors that influence growth rates of plant-parasitic nematodes.     

Quantification of strains in biaxially tested soft tissues

A technique for the quantification of the strain field in the central region of biaxially tested planar soft tissues is presented. A vidicon-based image analysis system interfaced to a PDP 11/34 minicomputer is employed to track particles affixed to the specimen surface in real-time, from which the strains are inferred. Illustrative results are given for tests on excised canine pleural specimens on which four particles were affixed. The technique is applicable, however, to any planar soft tissue and any number of tracking particles. This procedure is recommended over previously used methods when testing anisotropic tissues.     

Differentiation of Cancellous Bone and Medullary Bone in Laying Hens: a Novel Technique for Image Analysis

A selective staining technique for the identification and differentiation of cancellous bone from medullary bone of the laying hen by image analysis is described. Undecalcified Polymaster resin sections were oxidized in acidified potassium permanganate and oxalic acid before being immersed in an ammoniacal silver solution. The sections were reduced in formalin, fixed in sodium thiosulfate and counterstained in naphthalene black 10B which was dissolved in picric and acetic acids. Intensely stained cancellous bone was prominent with this technique compared with a paler medullary bone component which permitted the former to be easily recognized and measured by image analysis.     

APPLICATION OF THE PDMPO TECHNIQUE IN STUDYING SILICA DEPOSITION IN NATURAL POPULATIONS OF FRAGILARIA CROTONENSIS (BACILLARIOPHYCEAE) AT DIFFERENT DEPTHS IN A EUTROPHIC RESERVOIR1

At weekly intervals from July to October 2006, we measured silica deposition in the summer diatom assemblage at various depths in the eutrophic ?ímov Reservoir (Czech Republic) using PDMPO, the 2‐(4‐pyridyl)‐5{[4‐(2‐dimethylaminoethyl‐aminocarbamoyl)‐methoxy]phenyl}oxazole labeling technique. Fluorescence microscopy coupled with image analysis allows quantifying silicon (Si) deposition over time and a simple distinction between cells that are actively depositing Si and those that are not. Diatom assemblage was exclusively dominated by Fragilaria crotonensis Kitton, which formed pronounced subsurface maxima (2–6.5 m). Concentrations of the main nutrients (Si and phosphorus, P) were low over the whole season; however, at depth, the nutrient availability was higher than at the surface. Fragilaria silica deposition rates were eight times higher at the surface than at depth. Half the population was involved in silica deposition at the surface, while only 20% active cells were doing so at depth. At the surface, silica deposition was limited by P deficiency; the effect of dissolved Si (DSi) was not statistically significant. Silica deposition at depth was significantly constrained by low light availability despite the 1% average light attenuation at depth, which is supposed sufficient for photosynthesis. This study represents the first attempt to employ the PDMPO technique coupled with quantitative image analysis of PDMPO fluorescence in freshwater ecology. On the basis of our results, PDMPO probe appears to be an appropriate proxy for the study of resource limitation in natural diatom populations.     

An improved method for detection and quantification of chitinase activities

Chitinases are enzymes that serve critical roles in fungal growth and development, in resistance of plants to fungal pathogens, and in parasitism of insects by entomopathogenic fungi. The term "chitinase" is used for 3 enzymatic activities: N-acetylglucosaminidases, which sequentially release N-acetylglucosamine residues from the chitin polymer; chitobiosidases, which release disaccharides; and endochitinases, which cleave within the polymer and release oligosaccharides. We describe a technique where chitinases are separated on non-denaturing polyacrylamide gels, activities are visualized and characterized with chitinase specific substrates, and specific activities are estimated by image analysis. This technique permits a rapid determination of all of the types of chitinases present within a sample as well as their activities.     

Quantitation of membrane receptor distributions by image correlation spectroscopy: concept and application.

Measurement of receptor distributions on cell surfaces is one important aspect of understanding the mechanism whereby receptors function. In recent years, scanning fluorescence correlation spectroscopy has emerged as an excellent tool for making quantitative measurements of cluster sizes and densities. However, the measurements are slow and usually require fixed preparations. Moreover, while the precision is good, the accuracy is limited by the relatively small amount of information in each measurement, such that many are required. Here we present a novel extension of the scanning correlation spectroscopy that solves a number of the present problems. The new technique, which we call image correlation spectroscopy, is based on quantitative analysis of confocal scanning laser microscopy images. Since these can be generated in a matter of a second or so, the measurements become more rapid. The image is collected over a large cell area so that more sampling is done, improving the accuracy. The sacrifice is a lower resolution in the sampling, which leads to a lower precision. This compromise of precision in favor of speed and accuracy still provides an enormous advantage for image correlation spectroscopy over scanning correlation spectroscopy. The present work demonstrates the underlying theory, showing how the principles can be applied to measurements on standard fluorescent beads and changes in distribution of receptors for platelet-derived growth factor on human foreskin fibroblasts.     

Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface‐associated marine species: a case study on reef sharks Carcharhinus melanopterus shoaling behaviour

A novel image analysis‐based technique applied to unmanned aerial vehicle (UAV) survey data is described to detect and locate individual free‐ranging sharks within aggregations. The method allows rapid collection of data and quantification of fine‐scale swimming and collective patterns of sharks. We demonstrate the usefulness of this technique in a small‐scale case study exploring the shoaling tendencies of blacktip reef sharks Carcharhinus melanopterus in a large lagoon within Moorea, French Polynesia. Using our approach, we found that C. melanopterus displayed increased alignment with shoal companions when distributed over a sandflat where they are regularly fed for ecotourism purposes as compared with when they shoaled in a deeper adjacent channel. Our case study highlights the potential of a relatively low‐cost method that combines UAV survey data and image analysis to detect differences in shoaling patterns of free‐ranging sharks in shallow habitats. This approach offers an alternative to current techniques commonly used in controlled settings that require time‐consuming post‐processing effort.     

Motion determination in actin filament fluorescence images with a spatio-temporal orientation analysis method

We present a novel approach of automatically measuring motion in series of microscopic fluorescence images. As a differential method, the three-dimensional structure tensor technique is used to calculate the displacement vector field for every image of the sequence, from which the velocities are subsequently derived. We have used this method for the analysis of the movement of single actin filaments in the in vitro motility assay, where fluorescently labeled actin filaments move over a myosin decorated surface. With its fast implementation and subpixel accuracy, this approach is, in general, very valuable for analyzing dynamic processes by image sequence analysis.     

Spline-based framework for interactive segmentation in biomedical imaging

Active contours constitute a computationally attractive framework for image segmentation. In this paper, we describe a fully parametric design that relies on B-spline bases and is specified by control points on the image. Our technique yields successful segmentation results even for challenging datasets where object contours are not well-defined. We can achieve this because our parametric approach uses few parameters and allows us to constrain the topology of the curve. We provide the details for an efficient implementation and discuss different design alternatives. This work comes with a companion software that gives the end user full control over the snakes. We demonstrate the features of our software which includes an interactive interface where the user can manipulate the position of control points by simple mouse actions.     

Spatial analysis of oblique photo‐point images for quantifying spatio‐temporal changes in plant communities

Question: Can spatial analytical techniques be used to extract quantitative measurements of vegetation communities from ground‐based permanent photo‐point images? Location: Mount Aspiring National Park, south‐western South Island, New Zealand. Methods: Sets of ground‐based photographs representing two contrasting vegetation types were selected to test two spatial analytical techniques. In the grid technique, a grid was superimposed onto the photographs and the frequency of species presence in each grid‐square was calculated to estimate species abundance/cover over the defined area. In the object‐oriented technique, the photographs were segmented into meaningful objects, based on the colour of the pixels and the textural patterns of the images, and the area occupied by an object in the image was used to derive species abundance/cover over the area. Results: Both techniques allow quick and easy classification of digital elements into ecologically relevant categories of vegetation components. The grid technique appeared more robust, being quick and efficient, accommodating all image types and providing presence/absence matrices for multivariate analysis. Fewer classes were identified using the object‐oriented technique, in particular for the forest interior site and for small individual plants such as Astelia spp. Conclusions: Both techniques showed potential for the objective quantitative analysis of long‐term vegetation monitoring of cover and changes of several component species, using repeat ground‐based photographs more specifically for grassland habitats. However, both rely to various degrees on manual classification. Corrective factors and strict protocols for taking the photographs are necessary to account for variation in view angles and to compute values more representative of absolute species abundance.     

A microcomputer system for video image analysis and diagnostic microdensitometry

A system for microdensitometry based on a microcomputer, video digitizer and solid-state camera has been developed. Image analysis and densitometry are achieved with convenient control over image editing and calibration. The linear photometric properties of the imaging device enable measurements of high accuracy. The system has proven to give rapid and repeatable performance for determining DNA content distribution from measurements of Feulgen-stained cell nuclei. The results show that a practical image analysis microdensitometer can be designed using a readily available microcomputer. The low cost and simple operation are of benefit for diagnostic applications in which flow cytometry is not possible, the time required for microscope photometry is too great or an automated image analyzer and support staff are not available.     

Evaluation of image analysis and laser granulometry for microbial cell sizing

A direct cell size measurement technique and an image analysis based sizing method were developed. The former consisted of a manual size measurement of the two-dimensional cell images on a video screen, with automatic data recording. This method was chosen as the reference. The latter, a semiautomatic method took advantage of a commercial computer program designed for image processing and particle morphology analysis. It gave average and median size values which were compatible with the manual method. However, the performance of these time consuming methods is limited. Hence, the laser granulometry technique, intrinsically far more powerful while capable of analysing millions of sample objects in a short time delay, was applied. The comparison revealed that this method gives too low size values, particularly in disagreement with the known dimensions of the bacterial (Zymomonas mobilis) cells. A size correction method was developed to realign the granulometry results ofZ. mobilis cell samples with those of the direct manual measurement method.     

An image-interpolation technique for the computation of optic flow and egomotion

 A technique for measuring the motion of a rigid, textured plane in the frontoparallel plane is developed and tested on synthetic and real image sequences. The parameters of motion – translation in two dimensions, and rotation about a previously unspecified axis perpendicular to the plane – are computed by a single-stage, non-iterative process which interpolates the position of the moving image with respect to a set of reference images. The method can be extended to measure additional parameters of motion, such as expansion or shear. Advantages of the technique are that it does not require tracking of features, measurement of local image velocities or computation of high-order spatial or temporal derivatives of the image. The technique is robust to noise, and it offers a simple, novel way of tackling the ‘aperture’ problem. An application to the computation of robot egomotion is also described. Received: 3 September 1993/Accepted in revised form: 16 April 1994     

Accurate Image Analysis of the Retina Using Hessian Matrix and Binarisation of Thresholded Entropy with Application of Texture Mapping

In this paper, we demonstrate a comprehensive method for segmenting the retinal vasculature in camera images of the fundus. This is of interest in the area of diagnostics for eye diseases that affect the blood vessels in the eye. In a departure from other state-of-the-art methods, vessels are first pre-grouped together with graph partitioning, using a spectral clustering technique based on morphological features. Local curvature is estimated over the whole image using eigenvalues of Hessian matrix in order to enhance the vessels, which appear as ridges in images of the retina. The result is combined with a binarized image, obtained using a threshold that maximizes entropy, to extract the retinal vessels from the background. Speckle type noise is reduced by applying a connectivity constraint on the extracted curvature based enhanced image. This constraint is varied over the image according to each region''s predominant blood vessel size. The resultant image exhibits the central light reflex of retinal arteries and veins, which prevents the segmentation of whole vessels. To address this, the earlier entropy-based binarization technique is repeated on the original image, but crucially, with a different threshold to incorporate the central reflex vessels. The final segmentation is achieved by combining the segmented vessels with and without central light reflex. We carry out our approach on DRIVE and REVIEW, two publicly available collections of retinal images for research purposes. The obtained results are compared with state-of-the-art methods in the literature using metrics such as sensitivity (true positive rate), selectivity (false positive rate) and accuracy rates for the DRIVE images and measured vessel widths for the REVIEW images. Our approach out-performs the methods in the literature.