934 resultados para COMPUTER-AIDED DIAGNOSIS


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A model of multiple criteria decision making is presented for selecting the “best” of a finite number of alternatives. Techniques of scoring the alternatives and weighting the criteria are combined with different evaluating procedures and amalgamated in an interactive algorithm. Application of this method for choosing the best tender in a competitive bidding is discussed and a case is presented in some detail.

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Introduction: Computer-Aided-Design (CAD) and Computer-Aided-Manufacture (CAM) has been developed to fabricate fixed dental restorations accurately, faster and improve cost effectiveness of manufacture when compared to the conventional method. Two main methods exist in dental CAD/CAM technology: the subtractive and additive methods. While fitting accuracy of both methods has been explored, no study yet has compared the fabricated restoration (CAM output) to its CAD in terms of accuracy. The aim of this present study was to compare the output of various dental CAM routes to a sole initial CAD and establish the accuracy of fabrication. The internal fit of the various CAM routes were also investigated. The null hypotheses tested were: 1) no significant differences observed between the CAM output to the CAD and 2) no significant differences observed between the various CAM routes. Methods: An aluminium master model of a standard premolar preparation was scanned with a contact dental scanner (Incise, Renishaw, UK). A single CAD was created on the scanned master model (InciseCAD software, V2.5.0.140, UK). Twenty copings were then fabricated by sending the single CAD to a multitude of CAM routes. The copings were grouped (n=5) as: Laser sintered CoCrMo (LS), 5-axis milled CoCrMo (MCoCrMo), 3-axis milled zirconia (ZAx3) and 4-axis milled zirconia (ZAx4). All copings were micro-CT scanned (Phoenix X-Ray, Nanotom-S, Germany, power: 155kV, current: 60µA, 3600 projections) to produce 3-Dimensional (3D) models. A novel methodology was created to superimpose the micro-CT scans with the CAD (GOM Inspect software, V7.5SR2, Germany) to indicate inaccuracies in manufacturing. The accuracy in terms of coping volume was explored. The distances from the surfaces of the micro-CT 3D models to the surfaces of the CAD model (CAD Deviation) were investigated after creating surface colour deviation maps. Localised digital sections of the deviations (Occlusal, Axial and Cervical) and selected focussed areas were then quantitatively measured using software (GOM Inspect software, Germany). A novel methodology was also explored to digitally align (Rhino software, V5, USA) the micro-CT scans with the master model to investigate internal fit. Fifty digital cross sections of the aligned scans were created. Point-to-point distances were measured at 5 levels at each cross section. The five levels were: Vertical Marginal Fit (VF), Absolute Marginal Fit (AM), Axio-margin Fit (AMF), Axial Fit (AF) and Occlusal Fit (OF). Results: The results of the volume measurement were summarised as: VM-CoCrMo (62.8mm3 ) > VZax3 (59.4mm3 ) > VCAD (57mm3 ) > VZax4 (56.1mm3 ) > VLS (52.5mm3 ) and were all significantly different (p presented as areas with different colour. No significant differences were observed at the internal aspect of the cervical aspect between all groups of copings. Significant differences (p< M-CoCrMo Internal Occlusal, Internal Axial and External Axial 2 ZAx3 > ZAx4 External Occlusal, External Cervical 3 ZAx3 < ZAx4 Internal Occlusal 4 M-CoCrMo > ZAx4 Internal Occlusal and Internal Axial The mean values of AMF and AF were significantly (p M-CoCrMo and CAD > ZAx4. Only VF of M-CoCrMo was comparable with the CAD Internal Fit. All VF and AM values were within the clinically acceptable fit (120µm). Conclusion: The investigated CAM methods reproduced the CAD accurately at the internal cervical aspect of the copings. However, localised deviations at axial and occlusal aspects of the copings may suggest the need for modifications in these areas prior to fitting and veneering with porcelain. The CAM groups evaluated also showed different levels of Internal Fit thus rejecting the null hypotheses. The novel non-destructive methodologies for CAD/CAM accuracy and internal fit testing presented in this thesis may be a useful evaluation tool for similar applications.

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Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

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Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

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This report is the product of a first-year research project in the University Transportation Centers Program. This project was carried out by an interdisciplinary research team at The University of Iowa's Public Policy Center. The project developed a computerized system to support decisions on locating facilities that serve rural areas while minimizing transportation costs. The system integrates transportation databases with algorithms that specify efficient locations and allocate demand efficiently to service regions; the results of these algorithms are used interactively by decision makers. The authors developed documentation for the system so that others could apply it to estimate the transportation and route requirements of alternative locations and identify locations that meet certain criteria with the least cost. The system was developed and tested on two transportation-related problems in Iowa, and this report uses these applications to illustrate how the system can be used.

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This article describes the design and implementation of computer-aided tool called Relational Algebra Translator (RAT) in data base courses, for the teaching of relational algebra. There was a problem when introducing the relational algebra topic in the course EIF 211 Design and Implementation of Databases, which belongs to the career of Engineering in Information Systems of the National University of Costa Rica, because students attending this course were lacking profound mathematical knowledge, which led to a learning problem, being this an important subject to understand what the data bases search and request do RAT comes along to enhance the teaching-learning process.It introduces the architectural and design principles required for its implementation, such as: the language symbol table, the gramatical rules and the basic algorithms that RAT uses to translate from relational algebra to SQL language. This tool has been used for one periods and has demonstrated to be effective in the learning-teaching process.  This urged investigators to publish it in the web site: www.slinfo.una.ac.cr in order for this tool to be used in other university courses.

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Melanoma is a type of skin cancer and is caused by the uncontrolled growth of atypical melanocytes. In recent decades, computer aided diagnosis is used to support medical professionals; however, there is still no globally accepted tool. In this context, similar to state-of-the-art we propose a system that receives a dermatoscopy image and provides a diagnostic if the lesion is benign or malignant. This tool is composed with next modules: Preprocessing, Segmentation, Feature Extraction, and Classification. Preprocessing involves the removal of hairs. Segmentation is to isolate the lesion. Feature extraction is considering the ABCD dermoscopy rule. The classification is performed by the Support Vector Machine. Experimental evidence indicates that the proposal has 90.63 % accuracy, 95 % sensitivity, and 83.33 % specificity on a data-set of 104 dermatoscopy images. These results are favorable considering the performance of diagnosis by traditional progress in the area of dermatology

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To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.

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Considering the difficulties in finding good-quality images for the development and test of computer-aided diagnosis (CAD), this paper presents a public online mammographic images database free for all interested viewers and aimed to help develop and evaluate CAD schemes. The digitalization of the mammographic images is made with suitable contrast and spatial resolution for processing purposes. The broad recuperation system allows the user to search for different images, exams, or patient characteristics. Comparison with other databases currently available has shown that the presented database has a sufficient number of images, is of high quality, and is the only one to include a functional search system.

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A long-standing challenge of content-based image retrieval (CBIR) systems is the definition of a suitable distance function to measure the similarity between images in an application context which complies with the human perception of similarity. In this paper, we present a new family of distance functions, called attribute concurrence influence distances (AID), which serve to retrieve images by similarity. These distances address an important aspect of the psychophysical notion of similarity in comparisons of images: the effect of concurrent variations in the values of different image attributes. The AID functions allow for comparisons of feature vectors by choosing one of two parameterized expressions: one targeting weak attribute concurrence influence and the other for strong concurrence influence. This paper presents the mathematical definition and implementation of the AID family for a two-dimensional feature space and its extension to any dimension. The composition of the AID family with L (p) distance family is considered to propose a procedure to determine the best distance for a specific application. Experimental results involving several sets of medical images demonstrate that, taking as reference the perception of the specialist in the field (radiologist), the AID functions perform better than the general distance functions commonly used in CBIR.

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The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08º and 1.4º, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

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Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Imagem Digital com Radiação X.