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.     

How to convert a traditional electron microscopy laboratory to digital imaging: follow the 'middle road'

Today, electron microscopy (EM) is increasingly confronted by the revolution in image-processing technology provoked by modern computers. Digital cameras are fast replacing film-based cameras in EM, as elsewhere, and the procedures for digital image-archiving, image-analysis, and image publication are rapidly evolving. To take advantage of these advances, we have chosen for the moment a 'middle road', in which film remains our basic recording medium in the electron microscope, but immediately thereafter, all film-based images are converted to digital files for further analysis and processing. The rationale behind this approach is that film still offers far greater sensitivity and resolution (providing an image equivalent to> 10 000 pixels per inch in a 1-s exposure), and film is still far easier to organize and archive than digital images of comparable resolution. However, digital manipulation of EM images has become mandatory. Hence, we explain here, in some detail, how we convert from film to digital.     

Image analysis for monitoring the barley tempeh fermentation process

AIMS: To develop a fast, accurate, objective and nondestructive method for monitoring barley tempeh fermentation. METHODS AND RESULTS: Barley tempeh is a food made from pearled barley grains fermented with Rhizopus oligosporus. Rhizopus oligosporus growth is important for tempeh quality, but quantifying its growth is difficult and laborious. A system was developed for analysing digital images of fermentation stages using two image processing methods. The first employed statistical measures sensitive to image colour and surface structure, and these statistical measures were highly correlated (r=0.92, n=75, P<0.001) with ergosterol content of tempeh fermented with R. oligosporus and lactic acid bacteria (LAB). In the second method, an image-processing algorithm optimized to changes in images of final tempeh products was developed to measure number of visible barley grains. A threshold of 5 visible grains per Petri dish indicated complete tempeh fermentation. When images of tempeh cakes fermented with different inoculation levels of R. oligosporus were analysed the results from the two image processing methods were in good agreement. CONCLUSION: Image processing proved suitable for monitoring barley tempeh fermentation. The method avoids sampling, is nonintrusive, and only requires a digital camera with good resolution and image analysis software. SIGNIFICANCE AND IMPACT OF THE STUDY: The system provides a rapid visualization of tempeh product maturation and qualities during fermentation. Automated online monitoring of tempeh fermentation by coupling automated image acquisition with image processing software could be further developed for process control.     

Imaging system for morphometric assessment of absorption or fluorescence in stained cells

An image acquisition and processing system has been developed for quantitative microscopy of absorption or fluorescence in stained cells. Three different light transducers are used in the system to exploit the best characteristics of these sensors for different biological measurements. A digital scanner, in the form of a linear array charge-coupled device (CCD), acquires data with high spatial and photometric resolution. A color (RGB) camera is employed when spectral information is required for the segmentation of cellular subcomponents. An image-intensified charged-injection device (CID) camera provides for very low light intensity measurements, primarily for fluorescence-labeled cells. Properties of these transducers, such as contrast transfer function, linearity, and photo-response nonuniformity, have been measured. Two dedicated image processing units were incorporated into the system. The front-end processor, based on a digital signal processor, provides functions such as object detection, raw image calibration, compression, artifact removal, and filtering. The second image processor is associated with the frame memory and includes a histogram processor, a dedicated arithmetic logic unit for image processing functions, and a graphics module for one-bit overlay functions. An interactive program was developed to acquire cell images and to experiment with a range of segmentation algorithms, feature extractions, and other image processing functions. The results of any image operation are displayed on the video monitor. Once a desired processing sequence is determined, the sequence may be stored to become part of a command library and can be executed thereafter as a single instruction.     

DScan - a high-performance digital scanning system for entomological collections

Here we describe a high-performance imaging system for creating high-resolution images of whole insect drawers. All components of the system are industrial standard and can be adapted to meet the specific needs of entomological collections. A controlling unit allows the setting of imaging area (drawer size), step distance between individual images, number of images, image resolution, and shooting sequence order through a set of parameters. The system is highly configurable and can be used with a wide range of different optical hardware and image processing software.     

Data acquisition and management software for camera trap data: A case study from the TEAM Network

Camera traps and the images they generate are becoming an essential tool for field biologists studying and monitoring terrestrial animals, in particular medium to large terrestrial mammals and birds. In the last five years, camera traps have made the transition to digital technology, where these devices now produce hundreds of instantly available images per month and a large amount of ancillary metadata (e.g., date, time, temperature, image size, etc.). Despite this accelerated pace in the development of digital image capture, field biologists still lack adequate software solutions to process and manage the increasing amount of information in a cost efficient way. In this paper we describe a software system that we have developed, called DeskTEAM, to address this issue. DeskTEAM has been developed in the context of the Tropical Ecology Assessment and Monitoring Network (TEAM), a global network that monitors terrestrial vertebrates. We describe the software architecture and functionality and its utility in managing and processing large amounts of digital camera trap data collected throughout the global TEAM network. DeskTEAM incorporates software features and functionality that make it relevant to the broad camera trapping community. These include the ability to run the application locally on a laptop or desktop computer, without requiring an Internet connection, as well as the ability to run on multiple operating systems; an intuitive navigational user interface with multiple levels of detail (from individual images, to whole groups of images) which allows users to easily manage hundreds or thousands of images; ability to automatically extract EXIF and custom metadata information from digital images to increase standardization; availability of embedded taxonomic lists to allow users to easily tag images with species identities; and the ability to export data packages consisting of data, metadata and images in standardized formats so that they can be transferred to online data warehouses for easy archiving and dissemination. Lastly, building these software tools for wildlife scientists provides valuable lessons for the ecoinformatics community.     

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.     

Computer‐automated bird detection and counts in high‐resolution aerial images: a review

Bird surveys conducted using aerial images can be more accurate than those using airborne observers, but can also be more time‐consuming if images must be analyzed manually. Recent advances in digital cameras and image‐analysis software offer unprecedented potential for computer‐automated bird detection and counts in high‐resolution aerial images. We review the literature on this subject and provide an overview of the main image‐analysis techniques. Birds that contrast sharply with image backgrounds (e.g., bright birds on dark ground) are generally the most amenable to automated detection, in some cases requiring only basic image‐analysis software. However, the sophisticated analysis capabilities of modern object‐based image analysis software provide ways to detect birds in more challenging situations based on a variety of attributes including color, size, shape, texture, and spatial context. Some techniques developed to detect mammals may also be applicable to birds, although the prevalent use of aerial thermal‐infrared images for detecting large mammals is of limited applicability to birds because of the low pixel resolution of thermal cameras and the smaller size of birds. However, the increasingly high resolution of true‐color cameras and availability of small unmanned aircraft systems (drones) that can fly at very low altitude now make it feasible to detect even small shorebirds in aerial images. Continued advances in camera and drone technology, in combination with increasingly sophisticated image analysis software, now make it possible for investigators involved in monitoring bird populations to save time and resources by increasing their use of automated bird detection and counts in aerial images. We recommend close collaboration between wildlife‐monitoring practitioners and experts in the fields of remote sensing and computer science to help generate relevant, accessible, and readily applicable computer‐automated aerial photographic census techniques.     

A GPU Simulation Tool for Training and Optimisation in 2D Digital X-Ray Imaging

Conventional radiology is performed by means of digital detectors, with various types of technology and different performance in terms of efficiency and image quality. Following the arrival of a new digital detector in a radiology department, all the staff involved should adapt the procedure parameters to the properties of the detector, in order to achieve an optimal result in terms of correct diagnostic information and minimum radiation risks for the patient. The aim of this study was to develop and validate a software capable of simulating a digital X-ray imaging system, using graphics processing unit computing. All radiological image components were implemented in this application: an X-ray tube with primary beam, a virtual patient, noise, scatter radiation, a grid and a digital detector. Three different digital detectors (two digital radiography and a computed radiography systems) were implemented. In order to validate the software, we carried out a quantitative comparison of geometrical and anthropomorphic phantom simulated images with those acquired. In terms of average pixel values, the maximum differences were below 15%, while the noise values were in agreement with a maximum difference of 20%. The relative trends of contrast to noise ratio versus beam energy and intensity were well simulated. Total calculation times were below 3 seconds for clinical images with pixel size of actual dimensions less than 0.2 mm. The application proved to be efficient and realistic. Short calculation times and the accuracy of the results obtained make this software a useful tool for training operators and dose optimisation studies.     

Widefield deconvolution epifluorescence microscopy combined with fluorescence in situ hybridization reveals the spatial arrangement of bacteria in sponge tissue

Widefield deconvolution epifluorescence microscopy (WDEM) combined with fluorescence in situ hybridization (FISH) was performed to identify and characterize single bacterial cells within sections of the mediterranean sponge Chondrosia reniformis. Sponges were embedded in paraffin wax or plastic prior to the preparation of thin sections, in situ hybridization and microscopy. Serial digital images generated by widefield epifluorescence microscopy were visualized using an exhaustive photon reassignment deconvolution algorithm and three-dimensional rendering software. Computer processing of series of images taken at different focal planes with the deconvolution technique provided deblurred three-dimensional images with high optical resolution on a submicron scale. Results from the deconvolution enhanced widefield microscopy were compared with conventional epifluorescent microscopical images. By the application of the deconvolution algorithm on digital image data obtained with widefield epifluorescence microscopy after FISH, the occurrence and spatial arrangement of Desulfovibrionaceae closely associated with micropores of Chondrosia reniformis could be visualized.     

Computerized image analysis as a tool to quantify infiltrating leukocytes: a comparison between high- and low-magnification images.

The purpose of the present study was to establish a rapid and reproducible method for quantification of tissue-infiltrating leukocytes using computerized image analysis. To achieve this, the staining procedure, the image acquisition, and the image analysis method were optimized. Because of the adaptive features of the human eye, computerized image analysis is more sensitive to variations in staining compared with manual image analysis. To minimize variations in staining, an automated immunostainer was used. With a digital scanner camera, low-magnification images could be sampled at high resolution, thus making it possible to analyze larger tissue sections. Image analysis was performed by color thresholding of the digital images based on values of hue, saturation, and intensity color mode, which we consider superior to the red, green, and blue color mode for analysis of most histological stains. To evaluate the method, we compared computerized analysis of images with a x100 or a x12.5 magnification to assess leukocytes infiltrating rat brain tumors after peripheral immunizations with tumor cells genetically modified to express rat interferon-gamma (IFN-gamma) or medium controls. The results generated by both methods correlated well and did not show any significant differences. The method allows efficient and reproducible processing of large tissue sections that is less time-consuming than conventional methods and can be performed with standard equipment and software.(J Histochem Cytochem 49:1073-1079, 2001)     

A red line not to cross: Evaluating the limitation and properness of gel image tuning procedures

Currently, results of gel electrophoresis are commonly documented in digital formats by image acquisition instruments. In this study, gel images tuned by a common image processing software package, Photoshop, were assessed to understand the transforming algorithms and their impacts on quantitative analysis. TotalLab 100, an electrophoresis gel image analysis software package, was applied for image quantitation and evaluation. The three most frequently used image tuning functions—adjustments of the brightness, contrast, and grayscale span (level) of images—were investigated using both data generated from a standard grayscale tablet and an actual electrophoresis gel image. The influences of these procedures were analyzed for the grayscale transformation between the input and output images. Although all three procedures differentially improved the visualization of the input image, adjusting the contrast of images disrupted the quantitative information because of its nonlinear transforming algorithm. Under certain conditions, adjusting the brightness or the level of images could preserve the quantitative information because of the linear transforming algorithms. It was found that when the minimum and maximum grayscales of a gel image were recognized, using a commercial software package to maximally stretch the level may significantly improve the quality of a gel image without jeopardizing quantitative analysis.     

Electronic light microscopy: present capabilities and future prospects

Electronic light microscopy involves the combination of microscopic techniques with electronic imaging and digital image processing, resulting in dramatic improvements in image quality and ease of quantitative analysis. In this review, after a brief definition of digital images and a discussion of the sampling requirements for the accurate digital recording of optical images, I discuss the three most important imaging modalities in electronic light microscopy-video-enhanced contrast microscopy, digital fluorescence microscopy and confocal scanning microscopy-considering their capabilities, their applications, and recent developments that will increase their potential. Video-enhanced contrast microscopy permits the clear visualisation and real-time dynamic recording of minute objects such as microtubules, vesicles and colloidal gold particles, an order of magnitude smaller than the resolution limit of the light microscope. It has revolutionised the study of cellular motility, and permits the quantitative tracking of organelles and gold-labelled membrane bound proteins. In combination with the technique of optical trapping (optical tweezers), it permits exquisitely sensitive force and distance measurements to be made on motor proteins. Digital fluorescence microscopy enables low-light-level imaging of fluorescently labelled specimens. Recent progress has involved improvements in cameras, fluorescent probes and fluorescent filter sets, particularly multiple bandpass dichroic mirrors, and developments in multiparameter imaging, which is becoming particularly important for in situ hybridisation studies and automated image cytometry, fluorescence ratio imaging, and time-resolved fluorescence. As software improves and small computers become more powerful, computational techniques for out-of-focus blur deconvolution and image restoration are becoming increasingly important. Confocal microscopy permits convenient, high-resolution, non-invasive, blur-free optical sectioning and 3D image acquisition, but suffers from a number of limitations. I discuss advances in confocal techniques that address the problems of temporal resolution, spherical and chromatic aberration, wavelength flexibility and cross-talk between fluorescent channels, and describe new optics to enhance axial resolution and the use of two-photon excitation to reduce photobleaching. Finally, I consider the desirability of establishing a digital image database, the BioImage database, which would permit the archival storage of, and public Internet access to, multidimensional image data from all forms of biological microscopy. Submission of images to the BioImage database would be made in coordination with the scientific publication of research results based upon these data. In the context of electronic light microscopy, this would be particularly useful for three-dimensional images of cellular structure and video sequences of dynamic cellular processes, which are otherwise hard to communicate. However, it has the wider significance of allowing correlative studies on data obtained from many different microscopies and from sequence and crystallographic investigations. It also opens the door to interactive hypermedia access to the multidimensional image data, and multimedia publishing ventures based upon this.Presented at the XXXVII Symposium of the Society for Histochemistry, 23 September 1995, Rigi Kaltbad, Switzerland     

Thin-section ratiometric Ca2+ images obtained by optical sectioning of fura-2 loaded mast cells

The availability of the ratiometric Ca2+ indicator dyes, fura-2, and indo-1, and advances in digital imaging and computer technology have made it possible to detect Ca2+ changes in single cells with high temporal and spatial resolution. However, the optical properties of the conventional epifluorescence microscope do not produce a perfect image of the specimen. Instead, the observed image is a spatial low pass filtered version of the object and is contaminated with out of focus information. As a result, the image has reduced contrast and an increased depth of field. This problem is especially important for measurements of localized Ca2+ concentrations. One solution to this problem is to use a scanning confocal microscope which only detects in focus information, but this approach has several disadvantages for low light fluorescence measurements in living cells. An alternative approach is to use digital image processing and a deblurring algorithm to remove the out of focus information by using a knowledge of the point spread function of the microscope. All of these algorithms require a stack of two-dimensional images taken at different focal planes, although the "nearest neighbor deblurring" algorithm only requires one image above and below the image plane. We have used a modification of this scheme to construct a simple inverse filter, which extracts optical sections comparable to those of the nearest neighbors scheme, but without the need for adjacent image sections. We have used this "no neighbors" processing scheme to deblur images of fura-2-loaded mast cells from beige mice and generate high resolution ratiometric Ca2+ images of thin sections through the cell. The shallow depth of field of these images is demonstrated by taking pairs of images at different focal planes, 0.5-microns apart. The secretory granules, which exclude the fura-2, appear in focus in all sections and distinct changes in their size and shape can be seen in adjacent sections. In addition, we show, with the aid of model objects, how the combination of inverse filtering and ratiometric imaging corrects for some of the inherent limitations of using an inverse filter and can be used for quantitative measurements of localized Ca2+ gradients. With this technique, we can observe Ca2+ transients in narrow regions of cytosol between the secretory granules and plasma membrane that can be less than 0.5-microns wide. Moreover, these Ca2+ increases can be seen to coincide with the swelling of the secretory granules that follows exocytotic fusion.     

Real-time multi-wavelength fluorescence imaging of living cells

We describe a new real-time fluorescence video microscope design for capturing intensified images of cells containing dual wavelength "ratio" dyes or multiple dyes. The microscope will perform real-time capture of two separate fluorescence emission images simultaneously, improving the time resolution of spatial distribution of fluorescence to video frame rates (30 frames/s or faster). Each emission wavelength is imaged simultaneously by one of two cameras, then digitized, background corrected and appropriately combined at standard video frame rates to be stored at high resolution on tape or digital video disk for further off-line analysis. Use of low noise, high sensitivity image intensifiers, coupled to CCD cameras produce stable, high contrast images using ultra low light levels with little persistence or bloom. The design has no moving parts in its optical train, which overcomes a number of technical difficulties encountered in the present filter wheel designs for multiple imaging. Coupled to compatible image processing software utilizing PC-AT computers, the new design can be built for a significantly lower cost than many presently available commercial machines. The system is ideal for ratio imaging applications; the software can calculate the ratio of fluorescence intensities pixel by pixel and provide the information to generate false-color images of the intensity data as well as other calculations based on the two images. Thus, it provides a powerful, inexpensive tool for studying the real-time kinetics of changes in living cells. Examples are presented for the kinetics of rapidly changing intracellular calcium detected by the calcium indicator probe indo-1 and the redistribution kinetics of multiple vital dyes placed in cells undergoing cell fusion.     

A maximum likelihood approach to two-dimensional crystals

Maximum likelihood (ML) processing of transmission electron microscopy images of protein particles can produce reconstructions of superior resolution due to a reduced reference bias. We have investigated a ML processing approach to images centered on the unit cells of two-dimensional (2D) crystal images. The implemented software makes use of the predictive lattice node tracking in the MRC software, which is used to window particle stacks. These are then noise-whitened and subjected to ML processing. Resulting ML maps are translated into amplitudes and phases for further processing within the 2dx software package. Compared with ML processing for randomly oriented single particles, the required computational costs are greatly reduced as the 2D crystals restrict the parameter search space. The software was applied to images of negatively stained or frozen hydrated 2D crystals of different crystal order. We find that the ML algorithm is not free from reference bias, even though its sensitivity to noise correlation is lower than for pure cross-correlation alignment. Compared with crystallographic processing, the newly developed software yields better resolution for 2D crystal images of lower crystal quality, and it performs equally well for well-ordered crystal images.     

Low-light imaging technology in the life sciences

Photon imaging is an increasingly important technique for the measurement and analysis of chemiluminescence and bioluminescence. New high-performance low-light level imaging systems have recently become available for the life science. These systems use advances in camera design and digital image processing and are now being used for a wide range of luminescence applications. They offer good sensitivity for photon detection and large dynamic range, and are suitable for quantitative analysis. This is achieved using a range of software techniques including image arithmetic, histogramming or summing regions of interest, feature extraction and multiple image processing for kinetics or assay screening. Improvements in imageprocessing hardware and software have increased the usefulness of these systems in the biosciences. Low-light imaging is a rapid and non-invasive method for the sensitive detection and analysis of luminescent assays. As such it offers a powerful and sensitive tool for investigating processes, both at the cellular level (luc and lux reporter genes, intracellular signalling) and for measurement of macro samples (immunoassays, gels and blots, tissue sections).     

A clockwork mollusc: Ultradian rhythms in bivalve activity revealed by digital photography

Time-lapse digital images can be acquired and archived using web-cameras, allowing non-invasive analysis of behavior patterns of bivalve molluscs at ultradian (sub-daily) time-scales over long intervals. These records can be analyzed directly by a human operator or through properly calibrated image analysis software. Preliminary results using species of marine and freshwater bivalves identify several ultradian biological rhythms of similar duration. Wavelet analysis indicates strong periodicity in mantle and siphon activity in the 3 to 7 min range, with longer duration shell contraction periods at 60-90 min. The recurrence of these rhythms among marine and freshwater bivalve species maintained under constant (but differing) conditions suggests the influence of common intrinsic drivers (chemico-physical mechanisms or biological clocks). Sub-daily growth increments preserved in the shells of rapidly growing bivalve species are potentially related to these biological rhythms, with implications for shell growth, biomineralization, and the temporal resolution of paleoclimate proxy data.     

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.