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PubMed2001

SignStream: a tool for linguistic and computer vision research on visual-gestural language data.

Research on recognition and generation of signed languages and the gestural component of spoken languages has been held back by the unavailability of large-scale linguistically annotated corpora of the kind that led to significant advances in the area of spoken language. A major obstacle has been the lack of computational tools to assist in efficient analysis and transcription of visual language data. Here we describe SignStream, a computer program that we have designed to facilitate transcription and linguistic analysis of visual language. Machine vision methods to assist linguists in detailed annotation of gestures of the head, face, hands, and body are being developed. We have been using SignStream to analyze data from native signers of American Sign Language (ASL) collected in our new video collection facility, equipped with multiple synchronized digital video cameras. The video data and associated linguistic annotations are being made publicly available in multiple formats.

Computer Simulation↗
PubMed1994

Evaluation of different image acquisition techniques for a computer vision system in the diagnosis of malignant melanoma.

BACKGROUND: Digital image analysis was found to be a useful technique for improved accuracy of preoperative diagnosis of melanocytic lesions. In previous studies digitized color slides were used as input for digital image analysis. New technologies and smaller video cameras made it possible to develop a camera system that allows the digitization of skin lesions directly from the patient. OBJECTIVE: We investigated whether conventional color slides or directly digitized images should be used for a reliable recognition of malignant melanoma. METHODS: Computer features describing characteristics of the lesions were computed for 404 digitized color slides and for 309 directly acquired lesions. Statistical analysis and classifier construction was performed by the commercial statistical classification program CART. RESULTS: With the data set derived either from the color slides or from the directly digitized lesions a sensitivity of about 90% for the recognition of malignant melanoma could be obtained. CONCLUSION: Both image acquisition techniques allow a reliable detection of malignant melanoma and both are appropriate as input for an image analysis system regarding its efficiency as a diagnostic tool. However, none of the classifiers can be applied with reasonable significance to both techniques.

Diagnosis, Computer-Assisted↗
PubMed2002

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↗
PubMedDate not supplied

Local macromolecular extravasation in thermal burns quantified by fluorescent video microscopy and computer vision.

A dorsal skin flap chamber model was developed for analysis of the microvascular response to moderate intensity local thermal burns. Fluorescein isothiocyanate tagged 70,000 d dextran was introduced to visualize the extravasation and interstitial transport of macromolecules at the burn site. Contact burns 0.5 cm in diameter were affected by touching a thermostated metal rod onto the exposed epidermal side of the chamber preparation. All burns were of 5-second duration at temperatures between 55 degrees C and 70 degrees C. Postburn leakage of the fluorescein-labeled probed was monitored at numerous sites in the preparation on a fluorescent microscope equipped with a low-light-level intensified silicon intensified target video camera and recorded on tape for subsequent quantitative analysis. Selected scenes were digitized and subjected to a sequence of computer-image processing operations to extract quantitative information about the concentration distribution and net accumulation of dextran in the interstitial space as a function of postburn time. A diffusion model based on cylindrical geometry was fit to the concentration profile data at each site analyzed, and an apparent diffusion coefficient describing the interstitial transport process was determined. The interstitial transport increased with burn temperature up to a threshold of 70 degrees C, where other factors resulted in significant reduction in the loss of fluorescent macromolecule from the vasculature.

Animals↗
PubMed2005

Analysis of esthetic smiles by using computer vision techniques.

Properly aligned teeth and a beautiful smile are the twin goals of orthodontic treatment. Unfortunately, a change in the smile arc is sometimes an unintended consequence of proper alignment. We used 3-dimensional dental models and visualization techniques, including curve-fitting and image-processing algorithms, to analyze smile arcs with respect to different parameters. The results show that smile consonance depends greatly on the conversational distance and the angle of elevation between the viewer and the smile.

Esthetics, Dental↗
PubMed1994

AIM Project A2003: COmputer VIsion in RAdiology (COVIRA).

This paper presents an overview of the COVIRA project, AIM Project No. 2003. The COVIRA consortium is performing research in the area of Multimodality Image Analysis, i.e., Registration and Segmentation. Together with results in the areas of Visualization, User Interface, Digital Anatomy Atlas, Conformal 3D Radiation Therapy Planning, and Cerebral Vessel Tree Reconstruction, clinical validation of initial results is under way at six clinical sites in five European countries. The main objective is to achieve an increase in efficiency and quality of healthcare in Neuro-radiological Diagnosis and Treatment Planning.

Anatomy, Artistic↗
PubMedDate not supplied

Skin cancer recognition by computer vision.

Automatic detection of several features characteristic of basal cell epitheliomas is described. The features selected for this feasibility study are semitranslucency, telangiectasia, ulcer, crust, and tumor border. Image processing methods used in this study include frequency analysis of the Fourier transform of the image, the Sun-Wee texture analysis algorithm, and several other image analysis techniques suitable for skin photographs. This image analysis software is designed for use with AI/DERM, an expert system that models diagnosis of skin tumors by dermatologists.

Basal Cell Carcinoma↗
PubMed2005

Computer vision elastography: speckle adaptive motion estimation for elastography using ultrasound sequences.

We present the development and validation of an image based speckle tracking methodology, for determining temporal two-dimensional (2-D) axial and lateral displacement and strain fields from ultrasound video streams. We refine a multiple scale region matching approach incorporating novel solutions to known speckle tracking problems. Key contributions include automatic similarity measure selection to adapt to varying speckle density, quantifying trajectory fields, and spatiotemporal elastograms. Results are validated using tissue mimicking phantoms and in vitro data, before applying them to in vivo musculoskeletal ultrasound sequences. The method presented has the potential to improve clinical knowledge of tendon pathology from carpel tunnel syndrome, inflammation from implants, sport injuries, and many others.

Algorithms↗
PubMed1999

Computer-vision-based extraction of neural dendrograms.

This work introduces a new approach to the characterization of neural cells by means of semi-automated generation of dendrograms; data structures which describe the inherently hierarchical nature of neuronal arborizations. Dendrograms describe the branched structure of neurons in terms of the length, average thickness and bending energy of each of the dendritic segments and allow in a straightforward manner, the inclusion of additional measures. The bending energy quantifies the complexity of the shape and can be used to characterize the spatial coverage of the arborizations (the bending energy is an alternative for other complexity measures such as the fractal dimension). The new approach is based on the partitioning of the cell's outer contour as a function of the high curvature points followed by a syntactical analysis of the segmented contours. The semi-automated method is robust and is an improvement on the time consuming manual generation of the dendrograms. Several experimental results are included in this paper which illustrate and corroborate the effectiveness of the approach. The technique presented in this paper is limited to planar neurons but could be extended to a 3D approach.

Algorithms↗
PubMed1985

Computer low vision aids.

Computers are invading all facets of optometric practice including low vision care. This brief paper will discuss indications for prescribing computer low vision aids, hardware and software currently available, and provide several short case reports to illustrate how the visually impaired individual can utilize this new technology.

Adult↗
PubMedDate not supplied

Computer-assisted neurosurgery system: Wayne State University hardware and software configuration.

Computer-assisted neurosurgery uses the latest technological advancements in imaging, computers, mechanics, and electronics to improve the accuracy and reduce the invasiveness and risk of neurosurgical procedures. We describe the Wayne State University, Detroit, Michigan, computer-assisted neurosurgical system with the emphasis on software and discuss the theory guiding the development of this system and its application in real-time position tracking systems. Our system consists of the Neurological Surgery Planning System (NSPS) software which we developed at our medical center and three types of position tracking systems: the Zamorano-Dujovny (Z-D) are digitizer for frame-based procedures, an articulated arm, and an infrared-based digitizer for frameless procedures. The NSPS software is designed to offer neurosurgeons a safe and accurate method to approach intracranial lesions by preoperatively planning a surgical trajectory. Software consisting of the most advanced technologies in computer vision, computer imaging/graphics, and stereotactic numeric analysis forms the core of the system. Capabilities for correlating data from imaging studies to facilitate image reconstruction, image mapping, and three-dimensional (3D) visualization of target volumes enable the neurosurgeon to simulate surgical procedures into a preoperative protocol to be used during surgery, both to follow the preplanned trajectory and to track the position of surgical instruments in real-time on the computer monitor. The tracking systems position and orient the surgical instruments relative to the patient's head. With these devices, the display of the surgical instruments together with the virtual images create an excellent intraoperative tool.

Algorithms↗
PubMed1994

Molecular surface recognition by a computer vision-based technique.

Correct docking of a ligand onto a receptor surface is a complex problem, involving geometry and chemistry. Geometrically acceptable solutions require close contact between corresponding patches of surfaces of the receptor and of the ligand and no overlap between the van der Waals spheres of the remainder of the receptor and ligand atoms. In the quest for favorable chemical interactions, the next step involves minimization of the energy between the docked molecules. This work addresses the geometrical aspect of the problem. It is assumed that we have the atomic coordinates of each of the molecules. In principle, since optimally matching surfaces are sought, the entire conformational space needs to be considered. As the number of atoms residing on molecular surfaces can be several hundred, sampling of all rotations and translations of every patch of a surface of one molecule with respect to the other can reach immense proportions. The problem we are faced with here is reminiscent of object recognition problems in computer vision. Here we borrow and adapt the geometric hashing paradigm developed in computer vision to a central problem in molecular biology. Using an indexing approach based on a transformation invariant representation, the algorithm efficiently scans groups of surface dots (or atoms) and detects optimally matched surfaces. Potential solutions displaying receptor--ligand atomic overlaps are discarded. Our technique has been applied successfully to seven cases involving docking of small molecules, where the structures of the receptor--ligand complexes are available in the crystallographic database and to three cases where the receptors and ligands have been crystallized separately. In two of these three latter tests, the correct transformations have been obtained.

Algorithms↗
PubMed1999

Efficient computational algorithms for docking and for generating and matching a library of functional epitopes II. Computer vision-based techniques for the generation and utilization of functional epitopes.

This is the second review in a two-part series. In the first review (1) we described the computational complexity involved in the docking of a ligand onto a receptor surface. In particular, we focused on efficient algorithms designed to handle this computational task. Such a procedure results in a large number of potential, geometrically feasible solutions. The difficulty is to pinpoint which of these is the more likely candidate. While there exists a number of approaches to rank these solutions according to different criteria, such as the size of the interface or some approximation of their binding energetics, none of the existing methods has been shown to be consistently successful in this endeavor. If the binding site is unknown a priori, the magnitude of the task is awesome. Here we propose one way of addressing this problem, i.e., via derivation and utilization of binding epitopes. If a library of such epitopes is available, particularly for a large number of protein families, it may be used to predict more likely binding sites for a given ligand. We describe an efficient, computer-vision based method to construct binding epitopes focusing on two ways through which such a library can be generated, (i) molecular surface-based, or (ii) residue-based. Alternatively, the two can be combined. We further describe how such a library may be used efficiently in the matching/docking procedure.

Algorithms↗