Automated radiographic diagnosis via feature extraction and classification of cardiac size and shape descriptors.
Explore the source record for details and available documents.
Computers↗
SEARCH · Search PubMed
Results for “Pattern Recognition, Automated”
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
CYBEST model 3 automated cytologic screening system for uterine cancer utilizing image analysis processing.
The improvements incorporated into the Model 3 version of CYBEST (Cyto-Biological Electronic Screening System) are highlighted. Following the successful development of a software-controlled automatic shading for a video system, the new Model 3 CYBEST contains a televisions scan system with a single-step, fine-resolution scan and strobe-light illumination in place of the two-step (coarse and fine) scan of Model 2. The automatic shading control is described in detail, as is the automated focusing system, which uses a touch-sensor to achieve a near-focus level and a differential adding algorithm to obtain exact focus. Improvements in the slide magazine and slide autochanger have quadrupled the number of slides that may be loaded into the machine at one time while increasing the speed of operation. CYBEST Model 3 has achieved our goal of rapid processing, requiring less than three minutes per specimen for final assessment as compared with the six minutes per specimen of Model 2. Field tests of Model 3 are currently under way, with a large number of smears prepared by our automated cell dispersion and monolayer smearing device (CYBEST-CDMS).
Cell Nucleus↗
Evaluation of an automated differential leukocyte counting system. I. Instrument description and reproducibility studies.
Explore the source record for details and available documents.
Computers↗
Evaluation of an automated differential leukocyte counting system. 3. Detection of abnormal cells.
Explore the source record for details and available documents.
Computers↗
LAVA--the system for all-ceramic ZrO2 crown and bridge frameworks.
All-ceramic restorations in the posterior region are an increasingly important area of dental care. However, no real suitable ceramics or economic processing procedures have been available so far. With the new LAVA system, it will be possible to satisfy these demands in the future. The system is based on the machining of presintered zirconia, which, due to its outstanding mechanical properties, its biocompatibility, and its excellent esthetics in combination with a specially designed veneer ceramic, is the ideal candidate for these applications. In combination with a corresponding CAD/CAM unit, the use of an easy-to-machine presintered ceramic material (which is sintered to full density after shaping, thus eliminating the need for extensive use of diamond tools) allows for the first time reliable, fully-automated and thus fast manufacturing of such restorations.
Cementation↗
Computer-based three-dimensional visualization of developmental gene expression.
A broad understanding of the relationship between gene activation, pattern formation and morphogenesis will require adequate tools for three-dimensional and, perhaps four-dimensional, representation and analysis of molecular developmental processes. We present a novel, computer-based method for the 3D visualization of embryonic gene expression and morphological structures from serial sections. The information from these automatically aligned 3D reconstructions exceeds that from single-section and whole-mount visualizations of in situ hybridizations. In addition, these 3D models of gene-expression patterns can become a central component of a future developmental database designed for the collection and presentation of digitized, morphological and gene-expression data. This work is accompanied by a web site (http://www.univie.ac.at/GeneEMAC).
Anatomy, Cross-Sectional↗
Tauberian-prony feature extraction technique for esophageal motility patterns.
For the esophageal contractile activity recorded during swallowing, a feature extraction scheme has been developed. It recognizes the time, duration, and amplitudes of local peaks for each peristaltic wave. The method is based on the Tauberian approximation for modeling waveforms as a sum of identically shaped pulses with different time delays and amplitudes. Initial conditions on the pulse properties are set and an optimal solution is sought. The method is completely automated and can be utilized for characterization and classification purposes.
Algorithms↗
Hierarchical active shape models, using the wavelet transform.
Active shape models (ASMs) are often limited by the inability of relatively few eigenvectors to capture the full range of biological shape variability. This paper presents a method that overcomes this limitation, by using a hierarchical formulation of active shape models, using the wavelet transform. The statistical properties of the wavelet transform of a deformable contour are analyzed via principal component analysis, and used as priors in the contour's deformation. Some of these priors reflect relatively global shape characteristics of the object boundaries, whereas, some of them capture local and high-frequency shape characteristics and, thus, serve as local smoothness constraints. This formulation achieves two objectives. First, it is robust when only a limited number of training samples is available. Second, by using local statistics as smoothness constraints, it eliminates the need for adopting ad hoc physical models, such as elasticity or other smoothness models, which do not necessarily reflect true biological variability. Examples on magnetic resonance images of the corpus callosum and hand contours demonstrate that good and fully automated segmentations can be achieved, even with as few as five training samples.
Algorithms↗
An automated microscope for quantitative cytology combining television image analysis and stage scanning microphotometry.
This paper describes an automated microscope developed for operation in conjunction with the Leyden Television Analysis System. It features automated control of magnification, illumination, movement of scanning stages, and fine focus. These functions are controlled by means of a microcomputer. This enables a flexible design and relieves the supervising computer of simple but time consuming tasks. The combination of an automated microscope and Leyden Television Analysis System provides a powerful tool in quantitative cytological research. The flexible design permits other microscopic functions to be added with relatively little effort.
Computers↗
Computer vision and digital imaging technology in melanoma detection.
With today's treatment options, melanoma cure rates can be improved only if the diagnosis is made early enough to allow for curative surgery. Since clinical signs of malignancy in a pigmented lesion are often ambiguous and even dermatology experts may misdiagnose melanoma, diagnostic tools and procedures have been developed to assist the clinician in the diagnostic workup. Epiluminescence microscopy or dermatoscopy is widely used to inspect the melanin reticulum at the epidermo-dermal junction zone for signs indicative of early tumor growth. With the help of computer technology, digital dermatoscopy systems have entered the diagnostic arena capable of accurately assessing skin surface features modeled along the ABCD criteria already used for clinical assessment of pigmented skin lesions. Today's technically refined computer-based systems provide sophisticated functionalities for automated feature extraction and lesion assessment for quantitative analysis, and may also be used for education and training purposes.
Dermis↗
Computer-aided classification of breast masses in ultrasonic B-scans using a multiparameter approach.
Classification of breast masses in ultrasonic B-scan images is undertaken using a multiparameter approach. The parameters are generated on the basis of a non-Rayleigh statistic model of the backscattered envelope from the breast tissue. They can be computed automatically with minimal clinical intervention once the location of the mass is known. A new discriminant is developed that combines these parameters linearly. It is seen that this new discriminant performs classification of masses into benign or malignant better than the classification by any one of the individual parameters. The data set studied consisted of 99 cases (70 patients with benign masses and 29 patients with malignant masses). The areas under the receiver operating characteristic (ROC) curves (Az) and statistical attributes of the areas were studied to establish the enhancement in performance. The Az value after combining all the parameters was found to be 0.8701. Upon combining this parameter with the level of suspicion (LOS) scores of a radiologist, the performance is further enhanced with an area under the (empirical) ROC of 0.94 having an operating point at a sensitivity of 0.965 and specificity of 0.87. It is suggested that this automated approach may hold promise as a means of classifying breast masses.
Algorithms↗
Finding relevant references to genes and proteins in Medline using a Bayesian approach.
MOTIVATION: Mining the biomedical literature for references to genes and proteins always involves a tradeoff between high precision with false negatives, and high recall with false positives. Having a reliable method for assessing the relevance of literature mining results is crucial to finding ways to balance precision and recall, and for subsequently building automated systems to analyze these results. We hypothesize that abstracts and titles that discuss the same gene or protein use similar words. To validate this hypothesis, we built a dictionary- and rule-based system to mine Medline for references to genes and proteins, and used a Bayesian metric for scoring the relevance of each reference assignment. RESULTS: We analyzed the entire set of Medline records from 1966 to late 2001, and scored each gene and protein reference using a Bayesian estimated probability (EP) based on word frequency in a training set of 137837 known assignments from 30594 articles to 36197 gene and protein symbols. Two test sets of 148 and 150 randomly chosen assignments, respectively, were hand-validated and categorized as either good or bad. The distributions of EP values, when plotted on a log-scale histogram, are shown to markedly differ between good and bad assignments. Using EP values, recall was 100% at 61% precision (EP=2 x 10(-5)), 63% at 88% precision (EP=0.008), and 10% at 100% precision (EP=0.1). These results show that Medline entries discussing the same gene or protein have similar word usage, and that our method of assessing this similarity using EP values is valid, and enables an EP cutoff value to be determined that accurately and reproducibly balances precision and recall, allowing automated analysis of literature mining results. .
Abstracting and Indexing↗
Localization and segmentation of aortic endografts using marker detection.
A method for localization and segmentation of bifurcated aortic endografts in computed tomographic angiography (CTA) images is presented. The graft position is determined by detecting radiopaque markers sewn on the outside of the graft. The user indicates the first and the last marker, whereupon the remaining markers are automatically detected. This is achieved by first detecting marker-like structures through second-order scaled derivative analysis, which is combined with prior knowledge of graft shape and marker configuration. The identified marker centers approximate the graft sides and, derived from these, the central axis. The graft boundary is determined by maximizing the local gradient in the radial direction along a deformable contour passing through both sides. Three segmentation methods were tested. The first performs graft contour detection in the initial CT-slices, the second in slices that were reformatted to be orthogonal to the approximated graft axis, and the third uses the segmentation from the second method to find a more reliable approximation of the axis and subsequently performs contour detection. The methods have been applied to ten CTA images and the results were compared to manual marker indication by one observer and region growing aided segmentation by three observers. Out of a total of 266 markers, 262 were detected. Adequate approximations of the graft sides were obtained in all cases. The best segmentation results were obtained using a second iteration orthogonal to the axis determined from the first segmentation, yielding an average relative volume of overlap with the expert segmentations of 92%, while the interexpert reproducibility is 95%. The averaged difference in volume measured by the automated method and by the experts equals the difference among the experts: 3.5%.
Anatomy, Cross-Sectional↗
Cytomorphologic results of preparation experiments for monolayer deposition of cervical material.
For automated prescreening methods by high resolution analysis serving as a detecting method in gynecologic mass screening programs a new monolayer deposition method of cervical material has been used. This method will be outlines briefly and the mode of evaluation as well as current cytomorphological findings will be presented. With regard to measurability of the slides prepared according to the new method a number of cytologic criteria were thought to be of particular importance. These criteria are delineated and compiled in a table. A form in which these criteria were listed was filled in by cytopathologists for each slide evaluated. When performing isolation and centrifugation procedures several new morphologic questions arose to the cytopathologist which can only partly be answered by now. If taking into account all criteria of evaluation it may be followed from the present experiences that slides of cervical material are much more suited for automated prescreening methods by high resolution analysis if prepared after isolation and centrifugation in macromolecular liquids than are conventional Papanicolaou smears or slides from suspensions with isolated cells that were not subjected to centrifugation procedures.
Cell Separation↗
Computer-assisted pattern recognition model for the identification of slowly growing mycobacteria including Mycobacterium tuberculosis.
We present a computerized pattern recognition model used to speciate mycobacteria based on their restriction fragment length polymorphism (RFLP) banding patterns. DNA fragment migration distances were normalized to minimize lane-to-lane variability of band location both within and among gels through the inclusion of two internal size standards in each sample. The computer model used a library of normalized RFLP patterns derived from samples of known origin to create a probability matrix which was then used to classify the RFLP patterns from samples of unknown origin. The probability matrix contained the proportion of bands that fell within defined migration distance windows for each species in the library of reference samples. These proportions were then used to compute the likelihood that the banding pattern of an unknown sample corresponded to that of each species represented in the probability matrix. As a test of this process, we developed an automated, computer-assisted model for the identification of Mycobacterium species based on their normalized RFLP banding patterns. The probability matrix contained values for the M. tuberculosis complex, M. avium, M. intracellulare, M. kansasii and M. gordonae species. Thirty-nine independent strains of known origin, not included in the probability matrix, were used to test the accuracy of the method in classifying unknowns: 37 of 39 (94.9%) were classified correctly. An additional set of 16 strains of known origin representing species not included in the model were tested to gauge the robustness of the probability matrix. Every sample was correctly identified as an outlier, i.e. a member of a species not included in the original matrix.(ABSTRACT TRUNCATED AT 250 WORDS)
DNA, Bacterial↗
Automated speech technology for gastrointestinal endoscopy reporting and image recording.
Endoscopic databases will not be used until they are more efficient than (but as easy for physicians to use as) traditional dictate-and-transcribe methods. VoiceGI, a voice recognition system for endoscopic data entry, editing, storage and retrieval, and for capturing and storage of endoscopic images, is efficient and easy to use.
Databases, Factual↗
Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images.
An automated computerized scheme has been developed for determination of the likelihood measure of malignancy of pulmonary nodules on low-dose helical CT (LDCT) images. Our database consisted of 76 primary lung cancers (147 slices) and 413 benign nodules (576 slices). With this automated computerized scheme, the location of a nodule was first indicated by a radiologist. The outline of the nodule was segmented automatically by use of a dynamic programming technique. Various objective features on the nodules were determined by use of outline analysis and image analysis, and the likelihood measure of malignancy was determined by use of linear discriminant analysis (LDA). The effect of many different combinations of features and the performance of LDA in distinguishing benign nodules from malignant ones were evaluated by means of receiver operating characteristic (ROC) analysis. The Az value (area under the ROC curve) obtained by the computerized scheme in distinguishing benign nodules from malignant ones was 0.828 when a single slice was employed for each of the nodules. However, the Az value was improved to 0.846 when multiple slices were used for determination of the likelihood measure of malignancy. The Az values obtained by the computerized scheme on LDCT images were significantly greater than the Az value of 0.70, which was obtained from our previous observer studies by radiologists in distinguishing benign nodules from malignant ones on LDCT images. The automated computerized scheme for determination of the likelihood measure of malignancy would be useful in assisting radiologists to distinguish between benign and malignant pulmonary nodules on LDCT images.
Algorithms↗
Automated interference refractometer: an algorithm for locating an irregular fringe pattern.
The interference refractometer is potentially a valuable instrument for the measurement of gas concentrations, but its usefulness has been limited by the necessity to locate visually a pattern of light and dark bands in order to obtain the reading. The instrument is therefore liable to human error and is unsuitable for continuous monitoring. An improved design has been patented, in which this location process is automated by the use of a microprocessor and an array of light-sensitive diodes. To implement this improvement it was necessary to design an algorithm which would reliably locate the pattern. This paper describes the approaches which were considered and the successful algorithm. Some examples are given to illustrate the power of the final algorithm to locate patterns even after severe distortion.
Algorithms↗