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At least 919 records · Page 51Linked to original sources
PubMed1996

Automatic centering of the microscope image for vitreoretinal surgery.

PURPOSE: The authors report on their device, the surgical image tracker, which provides automatic compensation for movements of the surgical image within the microscope field of view, during vitreoretinal procedures. METHODS: The authors developed a compact device acting as an automatic image tracker, based on video monitoring of the surgical image and translation of the operating microscope. Basic components are a standard color charge-coupled device camera and a specifically designed frame grabber for discrimination and tracking of the target image. Operation of the device is fully compatible with the usual pedal adjustments. RESULTS: Ready, fast, and correct automatic centering of the microscope field of view has been achieved successfully in all typical operating conditions. Video recording always is equally well centered. System operation also is effective with panoramic optics and diffuse illumination. CONCLUSION: The surgical image tracker appears to be a valuable tool to obtain well auto-centered surgical images, eliminating a bothersome task during vitreoretinal surgery.

Humans↗
PubMed2000

Precision of automatic measurements of pigmented skin lesion parameters with a MelaFind(TM) multispectral digital dermoscope.

The purpose of this study was to assess the precision of automatic computerized measurement of parameters that may be useful in the differentiation of malignant melanoma from benign pigmented skin lesions, and also to determine the feasibility of quantitative monitoring of skin lesions over time. Ten independent sequences of images were acquired with a MelaFind multispectral digital dermoscope for each of 12 benign or malignant pigmented skin lesions. The sequences of images were processed automatically to provide 10 independent measurements of the various parameters for each lesion. Parameters included lesion area, greatest 'diameter', perimeter, reflectance and asymmetry. The precision of each parameter determination was computed from the mean and standard deviation of the 10 measurements of that parameter. The relative errors in determining the lesion area, 'diameter' and perimeter were found to be 6%, 3% and 4%, respectively. Other lesion parameters that are used in differentiating melanomas from benign skin lesions were also analysed as a function of wavelength. In the blue band (about 430 nm) the relative error was about 7% for the mean lesion reflectance and about 7% for the asymmetry parameter. These results demonstrate the feasibility of using MelaFind for objective quantitative monitoring of changes in pigmented skin lesions over time. As suggested by some studies, such information is useful in the early detection of malignant melanoma. The results show that parameters obtained automatically from MelaFind images are sufficiently precise to allow pertinent parameters to be used to classify pigmented skin lesions.

Databases, Factual↗
PubMed2006

Predicting cardiac rehabilitation enrollment: the role of automatic physician referral.

BACKGROUND: Despite the established benefits of cardiac rehabilitation, evidence suggests referral to, and subsequent enrollment in, cardiac rehabilitation following a coronary event remains low (10-25%). The aim of this study was to identify predictors of attendance to cardiac rehabilitation intake and subsequent enrollment in rehabilitation after coronary artery bypass graft surgery within the framework of an automatic referral system. DESIGN AND METHODS: We conducted a historic prospective study of patients who underwent coronary artery bypass graft surgery between 1 April 1996 and 31 March 2000 and lived within the geographic referral area of a multi-disciplinary cardiac rehabilitation center in central-south Ontario, Canada. Coronary artery bypass graft surgery patients are automatically referred to cardiac rehabilitation at the time of hospital discharge. Consecutive health records of eligible patients were reviewed for medical history, cardiac risk factor profiles, and evidence of cardiac rehabilitation intake attendance and enrolment. RESULTS: A total of 3536 patients met eligibility criteria. Patients were predominantly male (79.1%), approximately 64 years of age, living with a spouse or a partner, English-speaking, retired and had multiple cardiac risk factors. Of eligible patients, 2121 (60.0%) attended the cardiac rehabilitation intake appointment. Of patients who attended cardiac rehabilitation intake 1463 (69%) enrolled in at least one cardiac rehabilitation service, based on their risk factor profile. Selected cardiac rehabilitation services were exercise training (n=1287; 88%), nutrition counseling (n=571; 39.0%), nursing care (n=546; 37.3%), and psychological intervention (n=223; 15.2%). CONCLUSIONS: An institutionalized, physician-endorsed system of automatic referral to cardiac rehabilitation resulted in higher rates of cardiac rehabilitation intake and enrollment following coronary artery bypass graft surgery than previously reported and should be adopted for all cardiac populations.

Aged↗
PubMedDate not supplied

Dorsoventral extension of the talairach transformation and its automatic calculation for magnetic resonance neuroimages.

The Talairach transformation (TT), the most prevalent method for brain normalization and atlas-to-data warping, is conceptually simple, fast and can be automated. Two problems with the TT in the clinical setting that are addressed in this article are reduced accuracy at the orbitofrontal cortex and upper corpus callosum (CC) and unsuitability for functional neurosurgery because of incomplete scanning. To increase dorsoventral accuracy, we introduce 2 additional landmarks: the top of the CC (SM) and the most ventral point of the orbitofrontal cortex on the midsagittal slab (IM). A method for their automatic calculation is proposed and validated against 55 diversified magnetic resonance (MR) imaging cases. The SM and IM landmarks are identified accurately and robustly in an automatic way. The average error of SM localization is 0.69 mm, and 91% of all cases have an error not greater than 1 mm. The average error of IM localization is 0.98 mm, approximately three quarters of cases have an error not greater than 1 mm, and 95% of all cases have an error not larger than 2 mm. The SM is correlated (R(2) = 0.72) with the most superior cortical landmark, whereas the IM is only loosely correlated (R(2) = 0.22) with the most inferior cortical landmark. On average, the original TT overlays the atlas axial plate at -24 on the orbitofrontal cortex as opposed to the correct plate at -28. Therefore, 1-dimensional ventral scaling in the original TT is insufficient to cope with variability in the orbitofrontal cortex. The key advantages of our approach are the preserved conceptual simplicity of the TT, fully automatic identification of the new landmarks, improved accuracy of the atlas-to-data match without compromising performance, and enabled TT use in functional neurosurgery when a dorsal part of the brain is not available in the scan.

Algorithms↗
PubMed1996

Automatic identification of papillary muscles in left-ventricular short-axis echocardiographic images.

An automatic method for identifying the location of the papillary muscles in two-dimensional (2-D) short-axis echocardiographic images is described. The technique uses both spatial and temporal information to identify the presence and track the location of the muscles in the left ventricle from end-diastole to end-systole. The three main steps of the method are spatial preprocessing, spatial processing, and temporal processing. The spatial preprocessing step includes a region of search estimation. The spatial processing step includes a papillary muscle existence test and an initial approximation of the papillary muscle points. The temporal processing includes motion-pattern evaluation and final papillary muscle location. The estimates of existence and position for the automatic method were compared with estimates made by an independent expert observer. Two hundred and ten frames, three taken from each of 70 image sequences, were evaluated. Since two regions of search were processed for each frame (one for the posterior-inferior and one for the anterior-lateral papillary muscle), a total of 420 approximations were made. Of this total, 340 automatic estimates were judged to be in close agreement with estimates made by the expert. Of the remaining 80 approximations, 54 estimates were made by the expert when the computer determined that no papillary muscle was present, 17 estimates provided poor results, and nine estimates were made by the computer when the observer concluded that no papillary muscle was present.

Algorithms↗
PubMed1999

Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part I, Methodology and validation on normal subjects.

The study presented in this paper tests the hypothesis that the combination of a global similarity transformation and local free-form deformations can be used for the accurate segmentation of internal structures in MR images of the brain. To quantitatively evaluate our approach, the entire brain, the cerebellum, and the head of the caudate have been segmented manually by two raters on one of the volumes (the reference volume) and mapped back onto all the other volumes, using the computed transformations. The contours so obtained have been compared to contours drawn manually around the structures of interest in each individual brain. Manual delineation was performed twice by the same two raters to test inter- and intrarater variability. For the brain and the cerebellum, results indicate that for each rater, contours obtained manually and contours obtained automatically by deforming his own atlas are virtually indistinguishable. Furthermore, contours obtained manually by one rater and contours obtained automatically by deforming this rater's own atlas are more similar than contours obtained manually by two raters. For the caudate, manual intra- and interrater similarity indexes remain slightly better than manual versus automatic indexes, mainly because of the spatial resolution of the images used in this study. Qualitative results also suggest that this method can be used for the segmentation of more complex structures, such as the hippocampus.

Algorithms↗
PubMed1999

Automatic retinal image registration scheme using global optimization techniques.

Retinal image registration is commonly required in order to combine the complementary information in different retinal modalities. In this paper, a new automatic scheme to register retinal images is presented and is currently tested in a clinical environment. The scheme considers the suitability and efficiency of different image transformation models and function optimization techniques, following an initial preprocessing stage. Three different transformation models--affine, bilinear and projective--as well as three optimization techniques--downhill simplex method, simulated annealing and genetic algorithms--are investigated and compared in terms of accuracy and efficiency. The registration of 26 pairs of Fluoroscein Angiography and Indocyanine Green Chorioangiography images with the corresponding Red-Free retinal images, showed the superiority of combining genetic algorithms with the affine and bilinear transformation models. A comparative study of the proposed automatic registration scheme against the manual method, commonly used in the clinical practice, is finally presented showing the advantage of the proposed automatic scheme in terms of accuracy and consistency.

Algorithms↗
PubMed2005

Adaptive model initialization and deformation for automatic segmentation of T1-weighted brain MRI data.

A fully automatic, two-step, T1-weighted brain magnetic resonance imaging (MRI) segmentation method is presented. A preliminary mask of parenchyma is first estimated through adaptive image intensity analysis and mathematical morphological operations. It serves as the initial model and probability reference for a level-set algorithm in the second step, which finalizes the segmentation based on both image intensity and geometric information. The Dice coefficient and Euclidean distance between boundaries of automatic results and the corresponding references are reported for both phantom and clinical MR data. For the 28 patient scans acquired at our institution, the average Dice coefficient was 98.2% and the mean Euclidean surface distance measure was 0.074 mm. The entire segmentation for either a simulated or a clinical image volume finishes within 2 min on a modern PC system. The accuracy and speed of this technique allow us to automatically create patient-specific finite element models within the operating room on a timely basis for application in image-guided updating of preoperative scans.

Algorithms↗
PubMedDate not supplied

A hill-climbing approach for automatic gridding of cDNA microarray images.

Image and statistical analysis are two important stages of cDNA microarrays. Of these, gridding is necessary to accurately identify the location of each spot while extracting spot intensities from the microarray images and automating this procedure permits high-throughput analysis. Due to the deficiencies of the equipment used to print the arrays, rotations, misalignments, high contamination with noise and artifacts, and the enormous amount of data generated, solving the gridding problem by means of an automatic system is not trivial. Existing techniques to solve the automatic grid segmentation problem cover only limited aspects of this challenging problem and require the user to specify the size of the spots, the number of rows and columns in the grid, and boundary conditions. In this paper, a hill-climbing automatic gridding and spot quantification technique is proposed which takes a microarray image (or a subgrid) as input and makes no assumptions about the size of the spots, rows, and columns in the grid. The proposed method is based on a hill-climbing approach that utilizes different objective functions. The method has been found to effectively detect the grids on microarray images drawn from databases from GEO and the Stanford genomic laboratories.

Algorithms↗
PubMed2006

Gray-level grouping (GLG): an automatic method for optimized image contrast enhancement--Part II: the variations.

This is Part II of the paper, "Gray-Level Grouping (GLG): an Automatic Method for Optimized Image Contrast Enhancement". Part I of this paper introduced a new automatic contrast enhancement technique: gray-level grouping (GLG). GLG is a general and powerful technique, which can be conveniently applied to a broad variety of low-contrast images and outperforms conventional contrast enhancement techniques. However, the basic GLG method still has limitations and cannot enhance certain classes of low-contrast images well, e.g., images with a noisy background. The basic GLG also cannot fulfill certain special application purposes, e.g., enhancing only part of an image which corresponds to a certain segment of the image histogram. In order to break through these limitations, this paper introduces an extension of the basic GLG algorithm, selective gray-level grouping (SGLG), which groups the histogram components in different segments of the grayscale using different criteria and, hence, is able to enhance different parts of the histogram to various extents. This paper also introduces two new preprocessing methods to eliminate background noise in noisy low-contrast images so that such images can be properly enhanced by the (S)GLG technique. The extension of (S)GLG to color images is also discussed in this paper. SGLG and its variations extend the capability of the basic GLG to a larger variety of low-contrast images, and can fulfill special application requirements. SGLG and its variations not only produce results superior to conventional contrast enhancement techniques, but are also fully automatic under most circumstances, and are applicable to a broad variety of images.

Algorithms↗
PubMed2006

Gray-level grouping (GLG): an automatic method for optimized image contrast enhancement--Part I: the basic method.

Contrast enhancement has an important role in image processing applications. Conventional contrast enhancement techniques either often fail to produce satisfactory results for a broad variety of low-contrast images, or cannot be automatically applied to different images, because their parameters must be specified manually to produce a satisfactory result for a given image. This paper describes a new automatic method for contrast enhancement. The basic procedure is to first group the histogram components of a low-contrast image into a proper number of bins according to a selected criterion, then redistribute these bins uniformly over the grayscale, and finally ungroup the previously grouped gray-levels. Accordingly, this new technique is named gray-level grouping (GLG). GLG not only produces results superior to conventional contrast enhancement techniques, but is also fully automatic in most circumstances, and is applicable to a broad variety of images. An extension of GLG, selective GLG (SGLG), and its variations will be discussed in Part II of this paper. SGLG selectively groups and ungroups histogram components to achieve specific application purposes, such as eliminating background noise, enhancing a specific segment of the histogram, and so on. The extension of GLG to color images will also be discussed in Part II.

Algorithms↗
PubMed2006

Automatic 3-D grayscale volume matching and shape analysis.

Recently, shape matching in three dimensions (3-D) has been gaining importance in a wide variety of fields such as computer graphics, computer vision, medicine, and biology, with applications such as object recognition, medical diagnosis, and quantitative morphological analysis of biological operations. Automatic shape matching techniques developed in the field of computer graphics handle object surfaces, but ignore intensities of inner voxels. In biology and medical imaging, voxel intensities obtained by computed tomography (CT), magnetic resonance imagery (MRI), and confocal microscopes are important to determine point correspondences. Nevertheless, most biomedical volume matching techniques require human interactions, and automatic methods assume matched objects to have very similar shapes so as to avoid combinatorial explosions of point. This article is aimed at decreasing the gap between the two fields. The proposed method automatically finds dense point correspondences between two grayscale volumes; i.e., finds a correspondent in the second volume for every voxel in the first volume, based on the voxel intensities. Mutiresolutional pyramids are introduced to reduce computational load and handle highly plastic objects. We calculate the average shape of a set of similar objects and give a measure of plasticity to compare them. Matching results can also be used to generate intermediate volumes for morphing. We use various data to validate the effectiveness of our method: we calculate the average shape and plasticity of a set of fly brain cells, and we also match a human skull and an orangutan skull.

Algorithms↗
PubMed2002

Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis.

The quantitative analysis of magnetic resonance imaging (MRI) data has become increasingly important in both research and clinical studies aiming at human brain development, function, and pathology. Inevitably, the role of quantitative image analysis in the evaluation of drug therapy will increase, driven in part by requirements imposed by regulatory agencies. However, the prohibitive length of time involved and the significant intraand inter-rater variability of the measurements obtained from manual analysis of large MRI databases represent major obstacles to the wider application of quantitative MRI analysis. We have developed a fully automatic "pipeline" image analysis framework and have successfully applied it to a number of large-scale, multicenter studies (more than 1,000 MRI scans). This pipeline system is based on robust image processing algorithms, executed in a parallel, distributed fashion. This paper describes the application of this system to the automatic quantification of multiple sclerosis lesion load in MRI, in the context of a phase III clinical trial. The pipeline results were evaluated through an extensive validation study, revealing that the obtained lesion measurements are statistically indistinguishable from those obtained by trained human observers. Given that intra- and inter-rater measurement variability is eliminated by automatic analysis, this system enhances the ability to detect small treatment effects not readily detectable through conventional analysis techniques. While useful for clinical trial analysis in multiple sclerosis, this system holds widespread potential for applications in other neurological disorders, as well as for the study of neurobiology in general.

Algorithms↗
PubMed2004

A hybrid fuzzy logic/constraint satisfaction problem approach to automatic decision making in simulation game models.

Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.

Algorithms↗
PubMed1990

Image analysis of Nissl-stained neuronal perikarya in the primary visual cortex of the rat: automatic detection and segmentation of neuronal profiles with nuclei and nucleoli.

An image analysing procedure for the morphometric characterization of cortical neurons in Nissl-stained brain sections is described. It consists of the automatic detection of cellular profiles and their compartments: cytoplasm, nucleus and nucleolus. The algorithm was designed to cope with the large morphological spectrum of cortical perikarya (e.g. geometrical properties of perikarya, staining intensities of cell compartments and nucleo-plasmic area-ratio) including pyramidal (Golgi-category I) and non-pyramidal (Golgi-category II) neurons. Clusters of cells were separated and non-neuronal structures (e.g. glia, endothelial cells) as well as tangential, non-nucleolated sections through neuronal perikarya recognized and excluded from further analysis without requiring interactive procedures. The performance of the profile recognition procedure was evaluated using 426 nucleolated and non-nucleolated profiles of different types of neurons in the primary visual cortex of the rat. Nucleolated profiles were recognized as such with a 91% accuracy, non-nucleolated profiles were rejected correctly in 90% of cases. After automatic segmentation and selection of nucleolated neuronal profiles from the microscopic field, a large set of quantitative morphological features including geometrical, densitometrical and textural parameters can be measured using high power light microscopy. This permits quantitative morphometric characterization of different neuronal types. This procedure is the first part of a system for the automatic classification of Nissl-stained cortical neurons.

Algorithms↗
PubMed2004

Automatic time perception in the human brain for intervals ranging from milliseconds to seconds.

Time perception in everyday life deals with various intervals. Here we investigated whether an automatic duration-discrimination mechanism in audition operates even for intervals of an order of seconds, by using the mismatch negativity (MMN), an index of automatic change detection in audition. In Experiment 1, occasional decrements of the duration of a repetitive "standard" tone elicited an MMN in subjects ignoring auditory stimulation, even with the standard-stimulus durations over a second. Nevertheless, the MMN amplitude was significantly diminished with standard-stimulus durations of 800 ms and above, despite the fact that a constant deviant versus standard duration ratio was used. Complementary experiments varying the interstimulus interval (Experiment 2) and the magnitude of duration change (Experiment 3) yielded corroborating results. The present results suggest that automatic duration discrimination in audition operates even for durations of the order of seconds; yet its optimum time scale might be of the order of milliseconds.

Acoustic Stimulation↗
PubMed1993

An automatic computerized bipolar coagulator for dermatologic surgery.

BACKGROUND: The problem with all bipolar diathermy equipment is the adherence of the tissue to the prongs of the forceps. OBJECTIVE AND METHODS: We describe a new computerized bipolar coagulator (Coa-Comp/M) with electronic feedback of the tissue impedance that automatically starts and shuts off coagulation thus preventing overheating, undue tissue damage and sticking of the forceps. The fully automation implies that no footswitch or handcontrol is necessary. The coagulator was tested during 2 years in advanced dermatologic surgery. RESULTS: A log memory recorded the number of coagulations according to effect and coagulation time. A power setting of 16W was appropriate for effective coagulation of most vessels; 99% of the coagulations were faster than 1.3 seconds necessitating automatic control for preventing sticking and charring. CONCLUSIONS: The automatic bipolar coagulator saves time and avoids sticking of the forceps. It is a useful tool in dermatologic surgery demanding repeated coagulations for hemostasis.

Dermatology↗
PubMed1987

Automatic control systems for the artificial heart and ventricular assist device.

Automatic control systems for the artificial heart (AH) and ventricular assist device were developed using selected criteria of effectiveness, a mathematical model of regulation, and noninvasive measures of the hemodynamic parameters. The Sinus IS2 system was developed for control of the AH; its main component is a high-speed servomechanism that provides for the generation of pneumatic pulses. The servomechanism is controlled by automatic regulation with pressure feedback. Mean aortic pressure was used as the primary regulated hemodynamic parameter. The systems were tested using both a physical model and a physiologic experiment. Contractile insufficiency of the left ventricle was simulated in testing the control system for circulatory assistance. The studies demonstrate that automatic control systems function effectively by providing normal blood circulation in both the resting state and in certain transient processes occurring in a real, dynamic circulatory system.

Assisted Circulation↗