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At least 181 records · Page 10Linked to original sources

PubMedDate not supplied

Camera virtual equivalent model 0.01 pixel detectors.

In computer vision, a standard approach to eliminate spatial distortion is to use a calibrated grid. We developed an original method using such a grid to establish an equivalence between any camera with inherent technical limitations (optic, solid-state sensor, digitizer) and a perfect virtual pinhole camera model. This bijection based on interpolation concepts takes all the deformations generated by the optical and electronical equipment into account (distortion, decentration, scale, and affinity ratios) without the need for their explicit determination. We propose a detection method of this grid image by the use of grey levels approximation surfaces particularly adapted to this problem. We obtained a good precision on real grid images with modelization errors standard deviation of about 0.007 pixels with an off-the-shelf 512 x 512 camera using 256 grey levels. Three interpolation methods are compared: bilinear, cross-ratio in projective coordinates and bicubic splines. We conclude from this study that, in distorted images, the use of the bicubic splines interpolation method is a good improvement.

Algorithms↗

PubMed2001

Automated counting of mammalian cell colonies.

Investigating the effect of low-dose radiation exposure on cells using assays of colony-forming ability requires large cell samples to maintain statistical accuracy. Manually counting the resulting colonies is a laborious task in which consistent objectivity is hard to achieve. This is true especially with some mammalian cell lines which form poorly defined or 'fuzzy' colonies, typified by glioma or fibroblast cell lines. A computer-vision-based automated colony counter is presented in this paper. It utilizes novel imaging and image-processing methods involving a modified form of the Hough transform. The automated counter is able to identify less-discrete cell colonies typical of these cell lines. The results of automated colony counting are compared with those from four manual (human) colony counts for the cell lines HT29, A172, U118 and IN1265. The results from the automated counts fall well within the distribution of the manual counts for all four cell lines with respect to surviving fraction (SF) versus dose curves, SF values at 2 Gy (SF2) and total area under the SF curve (Dbar). From the variation in the counts, it is shown that the automated counts are generally more consistent than the manual counts.

Automation↗

PubMed2001

Improvement of mammographic mass characterization using spiculation meausures and morphological features.

We are developing new computer vision techniques for characterization of breast masses on mammograms. We had previously developed a characterization method based on texture features. The goal of the present work was to improve our characterization method by making use of morphological features. Toward this goal, we have developed a fully automated, three-stage segmentation method that includes clustering, active contour, and spiculation detection stages. After segmentation, morphological features describing the shape of the mass were extracted. Texture features were also extracted from a band of pixels surrounding the mass. Stepwise feature selection and linear discriminant analysis were employed in the morphological, texture, and combined feature spaces for classifier design. The classification accuracy was evaluated using the area Az under the receiver operating characteristic curve. A data set containing 249 films from 102 patients was used. When the leave-one-case-out method was applied to partition the data set into trainers and testers, the average test Az for the task of classifying the mass on a single mammographic view was 0.83 +/- 0.02, 0.84 +/- 0.02, and 0.87 +/- 0.02 in the morphological, texture, and combined feature spaces, respectively. The improvement obtained by supplementing texture features with morphological features in classification was statistically significant (p = 0.04). For classifying a mass as malignant or benign, we combined the leave-one-case-out discriminant scores from different views of a mass to obtain a summary score. In this task, the test Az value using the combined feature space was 0.91 +/- 0.02. Our results indicate that combining texture features with morphological features extracted from automatically segmented mass boundaries will be an effective approach for computer-aided characterization of mammographic masses.

Automation↗

PubMed2000

Probing f-actin flow by tracking shape fluctuations of radial bundles in lamellipodia of motile cells.

We examined the dynamics of radial actin bundles based on time-lapse movies of polarized light images of living neuronal growth cones. Using a highly sensitive computer vision algorithm for tracking, we analyzed the small shape fluctuations of radial actin bundles that otherwise remained stationary in their positions in the growth cone lamellipodium. Using the tracking software, we selected target points on radial bundles and measured both the local bundle orientations and the lateral displacements between consecutive movie frames. We found that the local orientation and the lateral displacement of a target point are correlated. The correlation can be explained using a simple geometric relationship between the lateral travel of tilted actin bundles and the retrograde flow of f-actin structures. Once this relationship has been established, we have turned the table and used the radial bundles as probes to measure the velocity field of f-actin flow. We have generated a detailed map of the complex retrograde flow pattern throughout the lamellipodium. Such two-dimensional flow maps will give new insights into the mechanisms responsible for f-actin-mediated cell motility and growth.

Actins↗

PubMed1997

Automatic extraction and measurement of leukocyte motion in microvessels using spatiotemporal image analysis.

This paper describes a computer vision system for the automatic extraction and velocity measurement of moving leukocytes that adhere to microvessel walls from a sequence of images. The motion of these leukocytes can be visualized as motion along the wall contours. We use the constraint that the leukocytes move along the vessel wall contours to generate a spatiotemporal image, and the leukocyte motion is then extracted using the methods of spatiotemporal image analysis. The generated spatiotemporal image is processed by a special-purpose orientation-selective filter and a subsequent grouping process newly developed for this application. The orientation-selective filter is designed by considering the particular properties of the spatiotemporal image in this application in order to enhance only the traces of leukocytes. In the subsequent grouping process, leukocyte trace segments are selected and grouped among all the segments obtained by simple thresholding and skeletonizing operations. We show experimentally that the proposed method can stably extract leukocyte motion.

Algorithms↗

PubMed1995

Three-dimensional reconstruction of the biliary tract from two-dimensional biliary images.

To make conventional two-dimensional cholangiography easier and more precise to read, we used techniques in computer vision to reconstruct the images in three dimensions. A 72-year-old man and a 70-year-old woman suffering from acute cholangitis were treated using endoscopic nasobiliary drainage. Their cholangiograms, from two orthogonal views, were used for three-dimensional reconstruction. We used video image-grabber and film scanner methods to digitize the original conventional biliary radiographs, and applied two different image processing methods to show the biliary structure. Both methods of three-dimensional reconstruction of the biliary tract were highly useful in evaluating the biliary tracts in these two patients, especially when a semitranslucence overlapping display technique was applied in the second patient. With this technique, the biliary tree itself and the stones inside the common bile duct can be clearly delineated. The technique of three-dimensional reconstruction of biliary images can make the conventional cholangiographs more lifelike and has great potential in surgical simulation in the near future.

Aged↗

PubMed2001

A new approach of geodesic reconstruction for drusen segmentation in eye fundus images.

Segmentation of bright blobs in an image is an important problem in computer vision and particularly in biomedical imaging. In retinal angiography, segmentation of drusen, a yellowish deposit located on the retina, is a serious challenge in proper diagnosis and prevention of further complications. Drusen extraction using classic segmentation methods does not lead to good results. We present a new segmentation method based on new transformations we introduced in mathematical morphology. It is based on the search for a new class of regional maxima components of the image. These maxima correspond to the regions inside the drusen. We present experimental results for drusen extraction using images containing examples having different types and shapes of drusen. We also apply our segmentation technique to two important cases of dynamic sequences of drusen images. The first case is for tracking the average gray level of a particular drusen in a sequence of angiographic images during a fluorescein exam. The second case is for registration and matching of two angiographic images from widely spaced exams in order to characterize the evolution of drusen.

Fluorescein Angiography↗

PubMed1995

Core-based portal image registration for automatic radiotherapy treatment verification.

PURPOSE: Portal imaging is the most important quality assurance procedure for monitoring the reproducibility of setup geometry in radiation therapy. The role of portal imaging has become even more critical in recent years due to the migration of three-dimensional (3D) treatment planning technology, including high-precision conformal therapy, from the research setting to routine clinical practice. Unfortunately, traditional methods for acquiring and interpreting portal images suffer from a number of deficiencies that contribute to the well-documented observation that many setup errors go undetected, and some persist for a clinically significant portion of the prescribed dose. Significant improvements in both accuracy and efficiency of detecting setup errors can, in principle, be achieved by using automatic image registration for on-line screening of images obtained from electronic portal imaging devices (EPIDs). METHODS AND MATERIALS: This article presents recent developments in a method called core-based image analysis that shows great promise for achieving the desired improvements in error detection. Core-based image analysis is a fundamental computer vision method that is capable of exploiting the full power of EPIDs by providing for on-line detection of setup errors via automatic registration of user-selected anatomical structures. We describe a robust method for automatic portal image registration based on core analysis and demonstrate an approach for assessing both accuracy and precision of registration methods using realistic, digitally reconstructed portal radiographs (DRPRs) where truth is known. RESULTS: Automatic core-based analysis of a set of 20 DRPRs containing known, random field positioning errors was performed for a patient undergoing treatment for prostate cancer. In all cases, the reported translation was within 1 mm of the actual translation with mean absolute errors of 0.3 mm and standard deviations of 0.3 mm. In all cases, the reported rotation was within 0.6 degree of the actual rotation with a mean absolute error of 0.18 degree and a standard deviation of 0.23 degree. CONCLUSION: Our results, using digitally reconstructed portal radiographs that closely resemble clinical portal images, suggest that automatic core-based registration is suitable as an on-line screening tool for detecting and quantifying patient setup errors.

Humans↗

PubMed1996

Automatic multiparameter fluorescence imaging for determining lymphocyte phenotype and activation status in melanoma tissue sections.

A system has been developed that combines multiparameter fluorescence imaging and computer vision techniques to provide automatic phenotyping of multiple cell types in a single tissue section. This system identifies both the nuclear and cytoplasmic boundary of each cell. A routine based on the watershed algorithm has been developed to segment an image of Hoechst-stained nuclei with an accuracy of greater than 85%. Deformable splines initially positioned at the nuclear boundaries are applied to images of fluorescently labelled cell-surface antigens. The splines lock onto the peak fluorescence signal surrounding the cell, providing an estimate of the cell boundary. From measurements acquired at this boundary, each cell is classified according to antigen expression. The system has been piloted in biopsies from melanoma patients participating in a clinical trial of the antibody R24. Thin tissue sections have been stained with Hoechst and three different fluorescent antibodies to antigens that permit the typing and evaluation of activity of T-cells. Changes in the infiltrates evaluated by multiparameter imaging were consistent with results obtained by immunoperoxidase analysis. The multiparameter fluorescent technique enables simultaneous determination of multiple cell subsets and can provide the spatial relationships of each cell type within the tissue.

Antigens, CD↗

PubMed2002

A semi-localized elastic net for surface reconstruction of objects from multislice images.

The traveling salesman problem (TSP) is a prototypical problem of combinatorial optimization and, as such, it has received considerable attention from neural-network researchers seeking quick, heuristic solutions. An early stage in many computer vision tasks is the extraction of object shape from an image consisting of noisy candidate edge points. Since the desired shape will often be a closed contour, this problem can be viewed as a version of the TSP in which we wish to link only a subset of the points/cities (i.e. the "noisefree" ones). None of the extant neural techniques for solving the TSP can deal directly with this case. In this paper, we present a simple but effective modification to the (analog) elastic net of Durbin and Willshaw which shifts emphasis from global to local behavior during convergence, so allowing the net to ignore some image points. Unlike the original elastic net, this semi-localized version is shown to tolerate considerable amounts of noise. As an example practical application, we describe the extraction of "pseudo-3D" human lung outlines from multiple preprocessed magnetic resonance images of the torso. An effectiveness measure (ideally zero) quantifies the difference between the extracted shape and some idealized shape exemplar. Our method produces average effectiveness scores of 0.06 for lung shapes extracted from initial semi-automatic segmentations which define the noisefree case. This deteriorates to 0.1 when extraction is from a noisy edge-point image obtained fully-automatically using a feedforward neural network.

Algorithms↗

PubMedDate not supplied

A self-learning segmentation framework--the Taguchi approach.

The detection of object boundary is an interesting and challenging task in computer vision and medical image processing. The active contour model (snake model) has attracted much attention for object boundary detection in the past decade. However, due to the lack of understanding on the effect of different energy terms to the behavior of related objective functions for an image, the assignment of weights for different energy terms in this model is usually fulfilled empirically. Few discussions have been brought out specifically for assigning these weights automatically. In this paper, a novel self-learning segmentation framework, based on the snake model is proposed and applied to the detection of cardiac boundaries from ultrasonic images. The framework consists of a learning section and a detection section, and provides a training mechanism to obtain the weights from a desired object contour given manually. This mechanism first employs Taguchi's method to determine the weight ratios among distinct energy terms, followed by a weight refinement step with a genetic algorithm. The refined weights can be treated as the a priori knowledge embedded in the manually defined contour and be used for subsequent contour detection. Experiments with both synthetic and real echocardiac images were conducted with satisfactory outcomes. Results also show that the present method can be used to analyze successive images of the same object with only one training contour. Finally, the validity of the weight determining process was verified by the analysis of variance method (ANOVA).

Algorithms↗

PubMed1999

Contour tracking using a knowledge-based snake algorithm to construct three-dimensional pharyngeal bolus movement.

Videofluorography (VFG) using a barium-mixed bolus is in wide clinical use for assessing patients with swallowing disorders. VFG is usually done with both lateral (LA) and anterior-posterior (AP) views, most commonly in two separate sittings. A real-time, three-dimensional (3-D) representation of the evolution of a pharyngeal bolus and its volumetric information can potentially help clinicians analyze and visualize the kinematics of swallowing, dysphagia, and compensatory therapeutic strategies. Active contour models, also known as "Snakes," have been used to solve various image analysis and computer vision problems. We applied a Snake algorithm to automate in part the contour tracking and reconstruction of VFG images to visualize and quantitatively analyze the 3-D evolution of a pharyngeal bolus. To improve the accuracy of the Snake search, we provided the additional "knowledge" of the pharyngeal image itself, which served as an extra constraint to push the Snake curve toward the desired contour. VFG of pharyngeal bolus transport in a normal subject was recorded by using barium-mixed boluses (viscosity: 185 centipoise, density: 2.84 g/cc) with volumes of 5, 10, and 20 ml. The resulting LA and AP video images were digitally captured and matched frame by frame. The knowledge-based Snake search algorithm was used to generate Snake points to satisfy both internal (i.e., smoothness) and external (i.e., boundary fitting) constraints. Using these Snake points, we traced the 3-D bolus movement at each time instant, assuming elliptic geometry in the cross-section of the pharyngeal bolus. By concentrating the 3-D images for each time instant, we developed a 3-D movie representing pharyngeal bolus movement. The efficiency, reproducibility, and accuracy of this algorithm in tracing pharyngeal bolus boundaries and estimating front/tail velocities were assessed and found satisfactory. We conclude that 3-D pharyngeal bolus movement can be traced both accurately and efficiently by using a knowledge-based Snake search algorithm.

Algorithms↗

PubMed1996

Detection of non-topological motifs in protein structures.

We present an efficient technique for the comparison of protein structures. The algorithm uses a vector representation of the secondary structure elements and searches for spatial configurations of secondary structure elements in proteins. In such recurring protein folds, the order of the secondary structure elements in the protein chains is disregarded. The method is based on the geometric hashing paradigm and implements approaches originating in computer vision. It represents and matches the secondary structure element vectors in a 3-D translation and rotation invariant manner. The matching of a pair of proteins takes on average under 3 s on a Silicon Graphics Indigo2 workstation, allowing extensive all-against-all comparisons of the data set of non-redundant protein structures. Here we have carried out such a comparison for a data set of over 500 protein molecules. The detection of recurring topological and non-topological, secondary structure element order-independent protein folds may provide further insight into evolution. Moreover, as these recurring folding units are likely to be conformationally favourable, the availability of a data set of such topological motifs can serve as a rich input for threading routines. Below, we describe this rapid technique and the results it has obtained. While some of the obtained matches conserve the order of the secondary structure elements, others are entirely order independent. As an example, we focus on the results obtained for Che Y, a signal transduction protein, and on the profilin-beta-actin complex. The Che Y molecule is composed of a five-stranded, parallel beta-sheet flanked by five helices. Here we show its similarity with the Escherichia coli elongation factor, with L-arabinose binding protein, with haloalkane dehalogenase and with adenylate kinase. The profilin-beta-actin contains an antiparallel beta-pleated sheet with alpha-helical termini. Its similarities to lipase, fructose disphosphatase and beta-lactamase are displayed.

Algorithms↗

PubMed2001

Automated tracking of facial features in patients with facial neuromuscular dysfunction.

Facial neuromuscular dysfunction severely impacts adaptive and expressive behavior and emotional health. Appropriate treatment is aided by quantitative and efficient assessment of facial motion impairment. We validated a newly developed method of quantifying facial motion, automated face analysis (AFA), by comparing it with an established manual marking method, the Maximal Static Response Assay (MSRA). In the AFA, motion of facial features is tracked automatically by computer vision without the need for placement of physical markers or restrictions of rigid head motion. Nine patients (seven women and two men) with a mean age of 39.3 years and various facial nerve disorders (five with Bell's palsy, three with trauma, and one with tumor resection) participated. The patients were videotaped while performing voluntary facial action tasks (brow raise, eye closure, and smile). For comparison with MSRA, physical markers were placed on facial landmarks. Image sequences were digitized into 640 x 480 x 24-bit pixel arrays at 30 frames per second (1 pixel congruent with0.3 mm). As defined for the MSRA, the coordinates of the center of each marker were manually recorded in the initial and final digitized frames, which correspond to repose and maximal response. For the AFA, these points were tracked automatically in the image sequence. Pearson correlation coefficients were used to evaluate consistency of measurement between manual (the MSRA) and automated (the AFA) tracking methods, and paired t tests were used to assess the mean difference between methods for feature tracking. Feature measures were highly consistent between methods, Pearson's r = 0.96 or higher, p < 0.001 for each of the action tasks. The mean differences between the methods were small; the mean error between methods was comparable to the error within the manual method (less than 1 pixel). The AFA demonstrated strong concurrent validity with the MSRA for pixel-wise displacement. Tracking was fully automated and provided motion vectors, which may be useful in guiding surgical and rehabilitative approaches to restoring facial function in patients with facial neuromuscular disorders.

Adult↗

PubMed2000

Division of labour and seasonality in the ant Leptothorax albipennis: worker corpulence and its influence on behaviour.

We address the organization of workers in social insect societies. We distinguish between changes in behavioural role over the nurse to forager role sequence, which may depend on changes in physiology, and potentially more rapid changes of task within role. We investigated the association between role and nutrient status in the ant Leptothorax albipennis. Worker lipid stores were quantified using a new body size-controlled method, and were related to worker behaviour. Worker lipid stores were evenly distributed amongst colony members at the end of winter, splitting rapidly into two distinct modes (replete nurses and lean foragers) in spring. The proportion of lean foragers increased throughout spring and summer, until most colonies contained only workers of this type. Callow workers then eclosed with intermediate lipid stores. We developed a computer vision system that tracks all nest ants to extract detailed behaviour of individuals of known lipid stores. Lipid storage was negatively correlated with a worker's foraging propensity, and with measures of spatial occupation in the nest and of activity. Different colonies showed a similar quantitative correlation between lipid stores and behavioural role, suggesting that lipid stores were not only correlated with the relative organization of individuals within each nest, but may also have influenced their absolute role. We reviewed the literature and found evidence that nutrient status influences role predisposition in social insect workers. We conclude that the distribution of worker roles may be linked to the balance between foraging income and energetic consumption within the colony directly via worker nutrient status. Copyright 2000 The Association for the Study of Animal Behaviour.

Journal Article↗

PubMed1996

A dataset of protein-protein interfaces generated with a sequence-order-independent comparison technique.

While there are a number of structurally non-redundant datasets of protein monomers, there is none of protein-protein interfaces. Yet, the availability of such a dataset is expected to provide an added insight into a number of investigations. First and foremost among these is analyzing the interfaces to obtain their prevailing architectures, the forces that account for the protein-protein associations and their packing considerations. Their comparisons with those of the monomers are likely to shed additional light on protein-protein recognition on the one hand and on the folding of the polypeptide chain on the other. Docking simulations are also expected to benefit from the existence of such a dataset. A major stumbling block to the generation of a dataset of interfaces has been that the interface is composed of at least two chains. Furthermore, in the interfaces, each of the chains might be represented by non-contiguous pieces. Their order in the interfaces being compared might be different as well. This discontinuity stems from the definition of an interface. An interface consists of interacting residues between the chains, and those that are in their vicinity in the supporting scaffold, within a certain distance threshold. This necessarily yields unordered fragments, as well as isolated residues. Our novel, efficient, sequence-order-independent structural comparison technique is ideally suited to handle the task of the generation of a library of structurally non-redundant protein-protein interfaces. As it is computer-vision based, it views atoms as collections of points in space, disregarding their chain connectivity. In this work, 351 interface-families are created. Comparisons of the interfaces, and separately, of the chains which contribute to them, yield some interesting cases. In one of the cases, while two interfaces are similar, the structure of only one of the two chains is similar between the two complexes. The structure of the second chain of the first complex differs from that of the second chain of the second complex. Here the structure of the cleft in the first chain dictates the specific binding interactions. In another case, while the interfaces in the two complexes are similar, both chains composing them differ between the complexes. Lastly, the chains composing the complexes are similar, but the interfaces are dissimilar, providing a set of data for investigations of the favorable orientations of protein-protein associations.

Algorithms↗

PubMed1996

Recognition-by-parts: a computational approach to human learning and generalization of shapes.

In this paper human pattern recognition is modeled in terms of how human observers learn to describe patterns in terms of their perceived parts, their unary (part) and binary (relational) attributes and the way in which such attribute states "evidence' different classes of shapes. This approach, originally developed in the area of computer vision, is concerned with algorithms which enable the learning of shape descriptions from examples and the classification of new data (generalization) efficiently and accurately. An object in such an "evidence-based' system is represented by a set of rules, where each rule provides a certain amount of evidence for each object class in the database. The accumulated class evidence over all activated rules can then be used to determine the classification probability. We have examined how well this model reflects human perception by training observers to classify compound Gabor patterns and then testing them with versions of such patterns which were segmented (gray-level transformed) versions of the original training set. If the observers were to construct rules to define each pattern class in terms of perceived parts and their relations, then it should be expected that classification performance would generalize to these new patterns from the original set. Results confirm this hypothesis and the specific feature extraction, learning and rule generation model used to predict performance.

Attention↗

PubMed2001

A fast method for calibrating video-based motion analysers using only a rigid bar.

Video-camera systems are widely used in biomechanics and clinical fields to measure the 3D kinematic measurements of human motion. To be used, they need to be calibrated, that is the parameters which geometrically define the cameras have to be determined. It is shown here how this can be achieved by surveying a rigid bar in motion inside the working volume, and in a very short time: less than 15 s on a Pentium III. The exterior parameters are estimated through the coplanarity constraint, the camera focal lengths through the properties of epipolar geometry and the principal points with a fast evolutionary optimisation which guarantees convergence when the initial principal points cannot be adequately estimated. The method has been widely tested on simulated and real data. Results show that its accuracy is comparable with that obtained using methods based on points of known 3D coordinates (DLT): 0.37 mm RMS error over a volume with a diagonal approximately 1.5 m. A preferential absolute reference system is obtained from the same bar motion data and is used to guide an intelligent decimation of the data. Finally, the role that the principal points play in achieving a high accuracy, which is questioned in the computer vision domain, is assessed through simulations.

Biomechanical Phenomena↗