MicroMeasure: a new computer program for the collection and analysis of cytogenetic data.

The ability to identify individual chromosomes in cytological preparations is an essential component of many investigations. While several computer software applications have been used to facilitate such quantitative karyotype analysis, most of these programs are limited by design for specific types of analyses, or can be used only with specific hardware configurations. MicroMeasure is a new image analysis application that may be used to collect data for a wide variety of chromosomal parameters from electronically captured or scanned images. Unlike similar applications, MicroMeasure may be individually configured by the end user to suit a wide variety of research needs. This program can be used with most common personal computers, and requires no unusual or specific hardware. MicroMeasure is made available to the research community without cost by the Department of Biology at Colorado State University via the World Wide Web at http://www.biology.colostate.edu/MicroMeasure.     

Computer-aided microtomography with true 3-D display in electron microscopy

A novel research system has been designed to permit three-dimensional (3-D) viewing of high resolution image data from transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The system consists of front-end primary data acquisition devices, such as TEM and SEM machines, which are equipped with computer-controlled specimen tilt stages. The output from these machines is in analogue form, where a video camera attached to the TEM provides the sequential analogue image output while the SEM direct video output is utilized. A 10 MHz digitizer transforms the video image to a digital array of 512 X 512 pixel units of 8 bits deep-stored in a frame buffer. Digital images from multiple projections are reconstructed into 3-D image boxes in a dedicated computer. Attached to the computer is a powerful true 3-D display device which has hardware for graphic manipulations including tilt and rotate on any axis and for probing the image with a 3-D cursor. Data editing and automatic contouring functions are used to enhance areas of interest, and specialized software is available for measurement of numbers, distances, areas, and volumes. With proper archiving of reconstructed image sequences, a dynamic 3-D presentation is possible. The microtomography system is highly versatile and can process image data on-line or from remote sites from which data records would typically be transported on computer tape, video tape, or floppy disk.     

Not seeing is not believing: improving the visibility of your fluorescence images

The digital age has brought both technical advances and ethical quandaries regarding data acquisition and image presentation in the field of cell biology. Image manipulation has drawn considerable attention in the past decade, leading to general guidelines for ethical data processing. However, effective methods of image presentation have been discussed only cursorily and have been largely overlooked. Under standard viewing conditions, the human visual system imposes limitations for readers analyzing fluorescence images. In this paper, I discuss the advantages and limitations of image-manipulation techniques with respect to the human visual system, including contrast stretching, nonlinear grayscale transformations, and pseudocoloring. While online data viewing presents innovative ways to access image information, most images continue to be viewed in static publications, in which image presentation is critical for effective information transmission.     

An Innovative Method for Obtaining Consistent Images and Quantification of Histochemically Stained Specimens

Obtaining digital images of color brightfield microscopy is an important aspect of biomedical research and the clinical practice of diagnostic pathology. Although the field of digital pathology has had tremendous advances in whole-slide imaging systems, little effort has been directed toward standardizing color brightfield digital imaging to maintain image-to-image consistency and tonal linearity. Using a single camera and microscope to obtain digital images of three stains, we show that microscope and camera systems inherently produce image-to-image variation. Moreover, we demonstrate that post-processing with a widely used raster graphics editor software program does not completely correct for session-to-session inconsistency. We introduce a reliable method for creating consistent images with a hardware/software solution (ChromaCal™; Datacolor Inc., NJ) along with its features for creating color standardization, preserving linear tonal levels, providing automated white balancing and setting automated brightness to consistent levels. The resulting image consistency using this method will also streamline mean density and morphometry measurements, as images are easily segmented and single thresholds can be used. We suggest that this is a superior method for color brightfield imaging, which can be used for quantification and can be readily incorporated into workflows.     

Development of a universal interface for the exchange of medical image data using magneto-optical media]

Digital images generated by medical imaging form the basis for radiological diagnosis and surgical planning. Despite the advent of the DICOM 3.0 standard for medical image communication, widespread application of the existing information is often limited by incompatibility of the data formatting used by different equipment generations, and the manufacturer-specific standards employed. An exchange interface based on magneto optical discs has been developed to retrieve and present medical image data regardless of the technological hardware and the specific formats used. Specially adapted routines to retrieve the data first had to be developed. A modular program structure was used to allow flexibility in the implementation of further routines and other exchange media. Over 20,000 CT and MRI images including header information obtained from different General Electric and Siemens scanners were extracted successfully from MO discs. The image data were used for follow up and surgical planning and were transferred to a PAC-server. The interface proved reliable and easy to use. Support for further proprietary formats is currently being developed. The present exchange interface permits reliable retrieval of digital images for diagnostic and surgical planning purposes, regardless of the hardware generation and manufacturer-specific formats.     

Formats of image data files that can be used for routine digital light micrography. Part one

Failing to open computer files that describe image data is not the most frustrating experience that the user of a computer can suffer, but it is high on list of possible aggravations. To ameliorate this, the structure of uncompressed image data files is described here. The various ways in which information that describes a picture can be recorded are related, and a primary distinction between raster or bitmap based and vector or object based image data files is drawn. Bitmap based image data files are the more useful of the two formats for recording complicated images such as digital light micrographs, whereas object based files are better for recording illustrations and cartoons. Computer software for opening a very large variety of different formats of digital image data is recommended, and if these fail, ways are described for opening bitmap based digital image data files whose format is unknown.     

Formats of image data files that can be used for routine digital light micrography. Part one

Failing to open computer files that describe image data is not the most frustrating experience that the user of a computer can suffer, but it is high on list of possible aggravations. To ameliorate this, the structure of uncompressed image data files is described here. The various ways in which information that describes a picture can be recorded are related, and a primary distinction between raster or bitmap based and vector or object based image data files is drawn. Bitmap based image data files are the more useful of the two formats for recording complicated images such as digital light micrographs, whereas object based files are better for recording illustrations and cartoons. Computer software for opening a very large variety of different formats of digital image data is recommended, and if these fail, ways are described for opening bitmap based digital image data files whose format is unknown.     

Development of a computer software for analysis of SDS-PAGE protein fingerprints of bacterial isolates

Protein fingerprinting is a widely used technique in epidemiological studies for typing bacterial strains. This study reports the development of a computer based gel analysis system. The system has the capability to analyse SDS-PAGE whole-cell protein profiles using digital image processing techniques. The software incorporates spatial and frequency domain operators for image enhancement, support for geometric correction of images and new algorithms for identification of strain tracks and protein bands. The system also provides facilities for correcting imaging defects for inter-gel comparison, similarity analysis, clustering and pictorial representation of results as a dendrogram. The software is highly interactive, user-friendly and can produce accurate results for differentiation of bacterial strains with minimal overhead of time.     

Mapping gold-labeled IgE receptors on mast cells by scanning electron microscopy: receptor distributions revealed by silver enhancement, backscattered electron imaging, and digital image analysis

Immunogold labeling and silver enhancement techniques are widely used to determine density and distribution of cell membrane receptors by light and transmission electron microscopy. However, these techniques have not been widely used for receptor detection by scanning electron microscopy. We used antigen- or protein A-conjugated colloidal gold particles, together with silver enhancement, sequential secondary and back-scattered electron imaging (SEI and BEI), and digital image processing, to explore cell surface distribution of IgE-receptor complexes on RBL-2H3 cells, a rat leukemia line that provides a model for the study of mucosal mast cells. Cells were first incubated with a monoclonal antidinitrophenol IgE (anti-DNP-IgE) that binds with high affinity to cell surface IgE receptors. The resulting IgE-receptor complexes were cross-linked either with the multivalent antigen, DNP-BSA-gold, or with a polyclonal anti-IgE antibody. Antibody-treated cells were labeled after fixation with protein A-gold. Fixed, gold-labeled cell monolayers were silver enhanced (or not), dehydrated, critical point-dried, and coated with gold-palladium (for SEI analysis) or carbon (for combined SEI/BEI analysis). They were observed in an Hitachi S800 SEM equipped with a field emission tip and a Robinson backscattered electron detector. An image processor (MegaVision 1024XM) digitized images directly from the S800 microscope at 500-1000 line resolution. Silver enhancement significantly improves detection of gold particles in both SEI and BEI modes of SEM. On gold-palladium-coated samples, 20-nm particles are resolved by SEI after enhancement. BEI resolves 15-nm particles without enhancement and 5- or 10-nm particles are resolved by BEI on silver-enhanced, carbon-coated samples. Neither BEI nor SEI alone can yield high resolution topographical maps of receptor distribution (BEI forms images on the basis of atomic number contrast which reveals gold but not surface features). Image analysis techniques were therefore introduced to digitize, enhance, and process BEI and SEI images of the same field of view. The resulting high-contrast, high-resolution images were superimposed, yielding well-resolved maps of the distribution of antigen-IgE-receptor complexes on the surface of RBL-2H3 mast cells. The maps are stored in digital form, as required for computer-based quantitative morphometric analyses. These techniques of silver enhancement, combined BEI/SEI imaging, and digital image analysis can be applied to analyze density and distribution of any gold-labeled ligand on its target cell.     

An image processing system for digital chest X-ray images

This paper investigates the requirements for image processing of digital chest X-ray images. These images are conventionally recorded on film and are characterised by large size, wide dynamic range and high resolution. X-ray detection systems are now becoming available for capturing these images directly in photoelectronic-digital form. In this report, the hardware and software facilities required for handling these images are described. These facilities include high resolution digital image displays, programmable video look up tables, image stores for image capture and processing and a full range of software tools for image manipulation. Examples are given of the application of digital image processing techniques to this class of image.     

Pattern recognition software and techniques for biological image analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.     

Software development of the EMI head scanner.

A method has been developed to run the general purpose operating system RDOS on the same disc of the head scanner computer as is used for scanner software and data. This made it possible to develop additional software in high level programming language for image processing, based on original image data on the disc. All new images produced by the program are stored on the disc in the same format as the original images. This makes it possible to handle processed images exactly as the original ones and to do multiple operations. The following processing has been included in the program so far: subtraction, smoothing, density profiles, vertical reconstructions, magnification and labelling. A set of operator commands has been developed which are very similar to the ordinary commands for the scanner, which makes the program to appear being a direct extension of the standard scanner software.     

daime, a novel image analysis program for microbial ecology and biofilm research

Combinations of microscopy and molecular techniques to detect, identify and characterize microorganisms in environmental and medical samples are widely used in microbial ecology and biofilm research. The scope of these methods, which include fluorescence in situ hybridization (FISH) with rRNA-targeted probes, is extended by digital image analysis routines that extract from micrographs important quantitative data. Here we introduce daime (digital image analysis in microbial ecology), a new computer program integrating 2-D and 3-D image analysis and visualization functionality, which has previously not been available in a single open-source software package. For example, daime automatically finds 2-D and 3-D objects in images and confocal image stacks, and offers special functions for quantifying microbial populations and evaluating new FISH probes. A novel feature is the quantification of spatial localization patterns of microorganisms in complex samples like biofilms. In combination with '3D-FISH', which preserves the 3-D structure of samples, this stereological technique was applied in a proof of principle experiment on activated sludge and provided quantitative evidence that functionally linked ammonia and nitrite oxidizers cluster together in their habitat. This image analysis method complements recent molecular techniques for analysing structure-function relationships in microbial communities and will help to characterize symbiotic interactions among microorganisms.     

A Modified DWT-SVD Algorithm for T1-w Brain MR Images Contrast Enhancement

BackgroundImage contrast enhancement is considered as the most useful technique permitting a better appearance of the low contrast images. This paper presents a modified Discret Wavelet Transform - Singular Value Decomposition (DWT-SVD) approach for the enhancement of low contrast Brain MR Images used for brain tissues exploration.MethodsThe proposed technique is processed as follows: first of all, we consider low contrast T1-weighted MRI slices as input images (A1) on which we apply General Histogram Equalization (GHE) algorithm to have equalized images referred as (A2) having zero as mean and one as variance. Secondly, by using the Discrete Wavelet Transform (DWT) algorithm, both (A1) and (A2) are divided into low and high frequency sub-bands. On the low frequency (LL1) and (LL2) sub-bands, SVD is processed in order to generate three matrix factorization (U, V and Σ) where the maximums of (U) and (V) matrix are used for the estimation of a correction coefficient (ξ). Our contribution in this paper is to estimate the new singular value matrix (New Σ) using a weighted sum of both original and equalized singular value matrix thanks to an adjustable parameter (μ) for the targeted low contrast images. This parameter, ranged between 0.05 and 0.95, is determined empirically according to the input low contrast image. Finally, the enhanced resulting image is easily reconstructed using the Inverse SVD (ISVD) and the Inverse DWT (IDWT) processes.ResultsThe database considered in our research consisted of 120 MR brain images where T1-weighted MR brain modality are selected for the contrast enhancement process. Considering the qualitative results, our proposed contrast enhancement method have shown better distinction between brain tissues and have preserved all White Matter (WM), Gray Matter (GM) and Cerebro-Spinal Fluid (CSF) pixel edges. In fact, histogram plots of images enhanced by proposed method covered all the gray level intensities. For the quantitative results, proposed method gives the highest PSNR, QRCM, SSIM, FSIM and EME values and the lowest AMBE values for (μ) equal to 0.65 as comparing to the rest of methods. These results signifies that proposed contrast enhancement method have provided greater image quality with preservation of image structure, feature and brightness.ConclusionProposed method improved performance of contrast enhancement image without creating unwanted artifact and without destroying image edge information or affecting the specificities of brain tissues. This is due to the use of an empirically (μ) parameter adjustable according to the input MR images. Hence, the proposed approach is appropriate for enhancing contrast of huge type of low contrast images.     

Assessing technician effects when extracting quantities from microscope images

Consider an experiment where the response is based on an image; e.g., an image captured to a computer file by a digital camera mounted on a microscope. Suppose relevant quantitative measures are extracted from the images so that results can be analyzed by conventional statistical methods. The steps involved in extracting the measures may require that the technicians, who are processing the images, perform some subjective manipulations. In this case, it is important to determine the bias and variability, if any, attributable to the technicians' decisions. This paper describes the experimental design and statistical analyses that are useful for those determinations. The design and analysis are illustrated by application to two biofilm research projects that involved quantitative image analysis. In one investigation, the technician was required to choose a threshold level, then the image analysis program automatically extracted relevant measures from the resulting black and white image. In the other investigation, the technician was required to choose fiducial points in each of two images collected on different microscopes; then the image analysis program registered the images by stretching, rotating, and overlaying them, so that their quantitative features could be correlated. These investigations elucidated the effects of the technicians' decisions, thereby helping us to assess properly the statistical uncertainties in the conclusions for the primary experiments.     

RADIONUCLIDE COMPUTED TOMOGRAPHY: APPLICATIONS IN CARDIOVASCULAR DISEASE

Tomography is an imaging modality in which information in one plane is displayed in focus while information from overlying and underlying planes is either blurred or eliminated. As a result, there is an improvement in the contrast of structures in the plane of interest. Computerized axial tomography (CAT) is an imaging modality in which a digital computer mathematically reconstructs the image of a plane or section from data collected perpendicular to the axis of that plane. The axis of the plane and the patient's long axis usually coincide so that the reconstructed images reveal transverse sections. In recent years, two types of computed tomography in medical imaging have generated a great deal of interest. These are X-ray transmission and radio-nuclide emission computed tomography.     

Experience in the application of Java Technologies in telemedicine

Java language has been demonstrated to be an effective tool in supporting medical image viewing in Russia. This evaluation was completed by obtaining a maximum of 20 images, depending on the client's computer workstation from one patient using a commercially available computer tomography (CT) scanner. The images were compared against standard CT images that were viewed at the site of capture. There was no appreciable difference. The client side is a lightweight component that provides an intuitive interface for end users. Each image is loaded in its own thread and the user can begin work after the first image has been loaded. This feature is especially useful on slow connection speed, 9.6 Kbps for example. The server side, which is implemented by the Java Servlet Engine works more effective than common gateway interface (CGI) programs do. Advantages of the Java Technology place this program on the next level of application development. This paper presents a unique application of Java in telemedicine.     

A new method for automatic metaphase finding adaptable to different chromosome preparations

A FORTRAN computer program, running on a Digital PDP 11-34 minicomputer, has been developed for use in conjunction with a Cambridge Quantimet 720 image analyzer for the investigation of metaphase preparations in routine cytogenetics. During a short initiation phase the program is adapted to the type of metaphase being analyzed. The program is fast and its performance is good, even at low microscopic magnifications. It has other uses in biology for all investigations and characterizations of small distinct elements widely spread within a preparation (e.g., autoradiography, bacteriology).     

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors.     

Videomicroscopy in the study of protoplasmic streaming and cell movement

Summary Various types of cell motility have been observed and analyzed with techniques of increasing sensitivity and sophistication. Photokymography, cinemicrography and laser-Doppler spectroscopy have all made important contributions to our knowledge of cytoplasmic streaming and cell movement.Now videomicroscopy is finding applications in recording and analyzing two different kinds of images. Video intensification microscopy by image intensifiers and silicon intensified target (SIT) video cameras is used to intensify images too dim to be viewed by eye or photographed. On the other hand, video enhanced microscopy uses a less sensitive chalnicon or other vidicon camera with adjustable amplification and offset to enhance the contrast and improve the resolution of microscopes that employ instrumental compensators.Both of these videotechniques have greatly extended the usefulness of the optical microscope: image intensification to brighten dim images and video enhancement to improve the contrast and resolution so that even submicroscopic structures and events can be recorded. These video techniques can both be further extended by a frame memory, with which images can be further enhanced by computer processing. Still to be developed, however, are appropriate methods for automatic tracking of particle motions.