PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “computer vision”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5Linked to original sources
PubMed2001

Modelling space perception in human early vision: a computational approach.

A computational approach in studying vision is important for understanding the biological mechanisms, as well as for integrating the known cortical architecture of primary visual area (V1) and the physiological functions (some of them experimentally proved, some only presumed). We present, in parallel, two models for early vision mechanisms: one for obtaining the disparity map in stereo vision, and the other for edges enhancement in contour integration, both of them seen from such a computational perspective. We implemented the two models and the results of the simulation were consistent with the biological data. They also account for the importance of interactions between parallel channels of visual information processing.

Computer Simulation↗
PubMedDate not supplied

Computer graphics visions and challenges: a European perspective.

I have briefly described important visions and challenges in computer graphics. They are a personal and therefore subjective selection. But most of these issues have to be addressed and solved--no matter if we call them visions or challenges or something else--if we want to make and further develop computer graphics into a key enabling technology for our IT-based society.

Computer Graphics↗
PubMed2006

A computer vision-based automated Figure-8 maze for working memory test in rodents.

The benchmark test for prefrontal cortex (PFC)-mediated working memory in rodents is a delayed alternation task utilizing variations of T-maze or Figure-8 maze, which requires the animals to make specific arm entry responses for reward. In this task, however, manual procedures involved in shaping target behavior, imposing delays between trials and delivering rewards can potentially influence the animal's performance on the maze. Here, we report an automated Figure-8 maze which does not necessitate experimenter-subject interaction during shaping, training or testing. This system incorporates a computer vision system for tracking, motorized gates to impose delays, and automated reward delivery. The maze is controlled by custom software that records the animal's location and activates the gates according to the animal's behavior and a control algorithm. The program performs calculations of task accuracy, tracks movement sequence through the maze, and provides other dependent variables (such as running speed, time spent in different maze locations, activity level during delay). Testing in rats indicates that the performance accuracy is inversely proportional to the delay interval, decreases with PFC lesions, and that animals anticipate timing during long delays. Thus, our automated Figure-8 maze is effective at assessing working memory and provides novel behavioral measures in rodents.

Algorithms↗
PubMed1992

Initial results for automated computational modeling of patient-specific electromagnetic hyperthermia.

Developments in finite-difference time-domain (FD-TD) computational modeling of Maxwell's equations, super-computer technology, and computed tomography (CT) imagery open the possibility of accurate numerical simulation of electromagnetic (EM) wave interactions with specific, complex, biological tissue structures. One application of this technology is in the area of treatment planning for EM hyperthermia. In this paper, we report the first highly automated CT image segmentation and interpolation scheme applied to model patient-specific EM hyperthermia. This novel system is based on sophisticated tools from the artificial intelligence, computer vision, and computer graphics disciplines. It permits CT-based patient-specific hyperthermia models to be constructed without tedious manual contouring on digitizing pads or CRT screens. The system permits in principle near real-time assistance in hyperthermia treatment planning. We apply this system to interpret actual patient CT data, reconstructing a 3-D model of the human thigh from a collection of 29 serial CT images at 10 mm intervals. Then, using FD-TD, we obtain 2-D and 3-D models of EM hyperthermia of this thigh due to a waveguide applicator. We find that different results are obtained from the 2-D and 3-D models, and conclude that full 3-D tissue models are required for future clinical usage.

Computer Simulation↗
PubMed2004

Frequency domain formulation of active parametric deformable models.

Active deformable models are simple tools, very popular in computer vision and computer graphics, for solving ill-posed problems or mimic real physical systems. The classical formulation is given in the spatial domain, the motor of the procedure is a second-order linear system, and rigidity and elasticity are the basic parameters for its characterization. This paper proposes a novel formulation based on a frequency-domain analysis: The internal energy functional and the Lagrange minimization are performed entirely in the frequency domain, which leads to a simple formulation and design. The frequency-based implementation offers important computational savings in comparison to the original one, a feature that is improved by the efficient hardware and software computation of the FFT algorithm. This new formulation focuses on the stiffness spectrum, allowing the possibility of constructing deformable models apart from the elasticity and rigidity-based original formulation. Simulation examples validate the theoretical results.

Journal Article↗
PubMedDate not supplied

Computers and vision.

Explore the source record for details and available documents.

Computer Terminals↗
PubMed1992

A man-machine vision interface for sensing the environment.

This study describes a computer vision approach for sensing the environment with the intent of helping people with a visual impairment. The principal goal in applying computer vision is to exploit, in an optimal fashion, the information acquired by the camera(s) to yield useful descriptions of the viewed environment. The objective is to seek efficient and reliable guidance cues in order to improve the mobility needs of individuals with a visual impairment. In this research direction, the following problems are identified and addressed: 1) the vision system design; 2) establishment of the mapping principles between the two-dimensional (2-D) camera images and the three-dimensional (3-D) real world; 3) development of appropriate imaging techniques for the interpretation of the 2-D images; and, 4) establishment of a communication link between the vision system and the user. The soundness of this research direction is assessed by means of a theoretical framework and experimental evaluations.

Algorithms↗
PubMedDate not supplied

Computational gestalts and perception thresholds.

In 1923, Max Wertheimer proposed a research programme and method in visual perception. He conjectured the existence of a small set of geometric grouping laws governing the perceptual synthesis of phenomenal objects, or "gestalt" from the atomic retina input. In this paper, we review this set of geometric grouping laws, using the works of Metzger, Kanizsa and their schools. In continuation, we explain why the Gestalt theory research programme can be translated into a Computer Vision programme. This translation is not straightforward, since Gestalt theory never addressed two fundamental matters: image sampling and image information measurements. Using these advances, we shall show that gestalt grouping laws can be translated into quantitative laws allowing the automatic computation of gestalts in digital images. From the psychophysical viewpoint, a main issue is raised: the computer vision gestalt detection methods deliver predictable perception thresholds. Thus, we are set in a position where we can build artificial images and check whether some kind of agreement can be found between the computationally predicted thresholds and the psychophysical ones. We describe and discuss two preliminary sets of experiments, where we compared the gestalt detection performance of several subjects with the predictable detection curve. In our opinion, the results of this experimental comparison support the idea of a much more systematic interaction between computational predictions in Computer Vision and psychophysical experiments.

Animals↗
PubMed2003

Digital image processing for biocompatibility studies of clinical implant materials.

The use of computer vision coupled with scanning electron microscopy (SEM) was used to monitor the platelet adhesion and activation onto blood-contacting materials. The interaction of blood platelets with polyethylene (PE), poly(ethylene terephthalate) (PET), and poly(vinylchloride) (PVC) after contact of the polymeric surfaces with whole blood was studied. The SEM images (SEM Phillips XL 30) were captured using HLImage++ computer vision systems. A library with a considerable number of acceptance or rejection of samples has been conceived and implemented. The obtained results make the developed computational vision system a promising tool for the evaluation of blood compatibility of biomaterials.

Algorithms↗
PubMed1998

A method for biomolecular structural recognition and docking allowing conformational flexibility.

In this work, we present an algorithm developed to handle biomolecular structural recognition problems, as part of an interdisciplinary research endeavor of the Computer Vision and Molecular Biology fields. A key problem in rational drug design and in biomolecular structural recognition is the generation of binding modes between two molecules, also known as molecular docking. Geometrical fitness is a necessary condition for molecular interaction. Hence, docking a ligand (e.g., a drug molecule or a protein molecule), to a protein receptor (e.g., enzyme), involves recognition of molecular surfaces. Conformational transitions by "hinge-bending" involves rotational movements of relatively rigid parts with respect to each other. The generation of docked binding modes between two associating molecules depends on their three dimensional structures (3-D) and their conformational flexibility. In comparison to the particular case of rigid-body docking, the computational difficulty grows considerably when taking into account the additional degrees of freedom intrinsic to the flexible molecular docking problem. Previous docking techniques have enabled hinge movements only within small ligands. Partial flexibility in the receptor molecule is enabled by a few techniques. Hinge-bending motions of protein receptors domains are not addressed by these methods, although these types of transitions are significant, e.g., in enzymes activity. Our approach allows hinge induced motions to exist in either the receptor or the ligand molecules of diverse sizes. We allow domains/subdomains/group of atoms movements in either of the associating molecules. We achieve this by adapting a technique developed in Computer Vision and Robotics for the efficient recognition of partially occluded articulated objects. These types of objects consist of rigid parts which are connected by rotary joints (hinges). Our method is based on an extension and generalization of the Hough transform and the Geometric Hashing paradigms for rigid object recognition. We show experimental results obtained by the successful application of the algorithm to cases of bound and unbound molecular complexes, yielding fast matching times. While the "correct" molecular conformations of the known complexes are obtained with small RMS distances, additional, predictive good-fitting binding modes are generated as well. We conclude by discussing the algorithm's implications and extensions, as well as its application to investigations of protein structures in Molecular Biology and recognition problems in Computer Vision.

Algorithms↗
PubMed1990

A two-dimensional analog VLSI circuit for detecting discontinuities in early vision.

A large number of computer vision algorithms for finding intensity edges, computing motion, depth, and color, and recovering the three-dimensional shape of objects have been developed within the framework of minimizing an associated "energy" or "cost" functional. Particularly successful has been the introduction of binary variables coding for discontinuities in intensity, optical flow field, depth, and other variables, allowing image segmentation to occur in these modalities. The associated nonconvex variational functionals can be mapped onto analog, resistive networks, such that the stationary voltage distribution in the network corresponds to a minimum of the functional. The performance of an experimental analog very-large-scale integration (VLSI) circuit implementing the nonlinear resistive network for the problem of two-dimensional surface interpolation in the presence of discontinuities is demonstrated; this circuit is implemented in complementary metal oxide semiconductor technology.

Algorithms↗
PubMed1990

Transparency and the uniqueness constraint in human and computer stereo vision.

The sensation of depth that is obtained with human binocular vision results from the differences in the projection of the world onto the two retinae. The process entails solving the problem of stereo correspondence, which involves choosing the correct matches between left and right image features. Many computational models of stereo vision assume a uniqueness constraint on stereo matching-that is, each feature identified in one image should eventually be matched with only one feature in the other image. This constraint would seem to be justified, as allowing non-unique matches would be tantamount to supposing that the scene entities to which matches relate are in two places at once. The value of the uniqueness constraint for eliminating false matches has been demonstrated in a variety of stereo algorithms. Yet on the basis of psychophysical results Weinshall concluded that it was not used by humans in dealing with certain types of ambiguous random-dot stereograms. We have now tested how Weinshall's stereograms are dealt with by PMF, a stereo algorithm which uses a unique-matches selection procedure in conjunction with a purely local similar-disparity support scheme. We found that PMF produces results that are closely analogous to the psychophysical results. This suggests that Weinshall's experiments should not be interpreted as evidence that the human stereo mechanism establishes non-unique matches.

Algorithms↗
PubMedDate not supplied

3D distance fields: a survey of techniques and applications.

A distance field is a representation where, at each point within the field, we know the distance from that point to the closest point on any object within the domain. In addition to distance, other properties may be derived from the distance field, such as the direction to the surface, and when the distance field is signed, we may also determine if the point is internal or external to objects within the domain. The distance field has been found to be a useful construction within the areas of computer vision, physics, and computer graphics. This paper serves as an exposition of methods for the production of distance fields, and a review of alternative representations and applications of distance fields. In the course of this paper, we present various methods from all three of the above areas, and we answer pertinent questions such as How accurate are these methods compared to each other? How simple are they to implement?, and What is the complexity and runtime of such methods?

Algorithms↗
PubMed1989

Computer simulations of figure-ground discrimination in the visual system of the fly.

Figure-ground discrimination and pattern discrimination represent one of the most important problems in computer vision. Based on computational neuronal network model proposed by Reichardt et al. for figure-ground discrimination in the visual system of the fly, entire systematic computer simulations were carried out under nonstationary conditions. Results show that the model network and simulations have predictive power for behavioural experimental results. This paper proposes that motion perception and elementary pattern discrimination in human visual system may be mediated by some kind of figure-ground system with movement detectors as input layer.

Animals↗
PubMed2002

Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model.

We have developed a model for FROC curve fitting that relates the observer's FROC performance not to the ROC performance that would be obtained if the observer's responses were scored on a per image basis, but rather to a hypothesized ROC performance that the observer would obtain in the task of classifying a set of "candidate detections" as positive or negative. We adopt the assumptions of the Bunch FROC model, namely that the observer's detections are all mutually independent, as well as assumptions qualitatively similar to, but different in nature from, those made by Chakraborty in his AFROC scoring methodology. Under the assumptions of our model, we show that the observer's FROC performance is a linearly scaled version of the candidate analysis ROC curve, where the scaling factors are just given by the FROC operating point coordinates for detecting initial candidates. Further, we show that the likelihood function of the model parameters given observational data takes on a simple form, and we develop a maximum likelihood method for fitting a FROC curve to this data. FROC and AFROC curves are produced for computer vision observer datasets and compared with the results of the AFROC scoring method. Although developed primarily with computer vision schemes in mind, we hope that the methodology presented here will prove worthy of further study in other applications as well.

Algorithms↗