881 resultados para Automated segmentation
Resumo:
The purpose of this project was to determine the feasibility of using pavement condition data collected for the Iowa Pavement Management Program (IPMP) as input to the Iowa Quadrennial Need Study. The need study, conducted by the Iowa Department of Transportation (Iowa DOT) every four years, currently uses manually collected highway infrastructure condition data (roughness, rutting, cracking, etc.). Because of the Iowa DOT's 10-year data collection cycles, condition data for a given highway segment may be up to 10 years old. In some cases, the need study process has resulted in wide fluctuations in funding allocated to individual Iowa counties from one study to the next. This volatility in funding levels makes it difficult for county engineers to plan and program road maintenance and improvements. One possible remedy is to input more current and less subjective infrastructure condition data. The IPMP was initially developed to satisfy the Intermodal Surface Transportation Efficiency Act (ISTEA) requirement that federal-aid-eligible highways be managed through a pavement management system. Currently all metropolitan planning organizations (MPOs) in Iowa and 15 of Iowa's 18 RPAs participate in the IPMP. The core of this program is a statewide data base of pavement condition and construction history information. The pavement data are collected by machine in two-year cycles. Using pilot areas, researchers examined the implications of using the automated data collected for the IPMP as input to the need study computer program, HWYNEEDS. The results show that using the IPMP automated data in HWYNEEDS is feasible and beneficial, resulting in less volatility in the level of total need between successive quadrennial need studies. In other words, the more current the data, the smaller the shift in total need.
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In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.
Resumo:
Kansas State University, with funding from the Kansas Department of Transportation (KDOT), has developed a computerized reduction system for profilograms produced by mechanical profilographs. The commercial version of the system (ProScan (trademark)) is marketed by Devore Systems, Inc. The system consists of an IBM Compatible PC 486SX33 computer or better, Epson LQ-570 printer, a Logitech Scanman 32 hand scanner system, a paper transport unit, and the ProScan software. The Scanner is not adaptable to IBM computers with the micro channel architecture. The Iowa DOT Transportation Centers could realize the following advantages by using ProScan: (1) Save about 5 to 8 staff hours of reduction and reporting time per Transportation Center per week for a Materials Technician 3 or 4 (the time savings would come during the busiest part of the season); (2) Reduce errors in reduction, transfer, and typing of profile values; (3) Increase the accuracy of the monitor results; and (4) Allow rapid evaluation of contractor traces when tolerance limits between monitor and certified results are exceeded.
Resumo:
This project examines similarities and differences between the automated condition data collected on and off county paved roads and the manual condition data collected by Iowa Department of Transportation (DOT) staff in 2000 and 2001. Also, the researchers will provide staff support to the advisory committee in exploring other options to the highway need process. The results show that the automated condition data can be used in a converted highway needs process with no major differences between the two methods. Even though the foundation rating difference was significant, the foundation rating weighting factor in HWYNEEDS is minimal and should not have a major impact. In terms of RUTF formula based distribution, the results clearly show the superiority of the condition-based analysis compared to the non-condition based. That correlation can be further enhanced by adding more distress variables to the analysis.
Resumo:
We propose to evaluate automatic three-dimensional gray-value rigid registration (RR) methods for prostate localization on cone-beam computed tomography (CBCT) scans. In total, 103 CBCT scans of 9 prostate patients have been analyzed. Each one was registered to the planning CT scan using different methods: (a) global RR, (b) pelvis bone structure RR, (c) bone RR refined by local soft-tissue RR using the CT clinical target volume (CTV) expanded with a 1, 3, 5, 8, 10, 12, 15 or 20-mm margin. To evaluate results, a radiation oncologist was asked to manually delineate the CTV on the CBCT scans. The Dice coefficients between each automatic CBCT segmentation - derived from the transformation of the manual CT segmentation - and the manual CBCT segmentation were calculated. Global or bone CT/CBCT RR has been shown to yield insufficient results in average. Local RR with an 8-mm margin around the CTV after bone RR was found to be the best candidate for systematically significantly improving prostate localization.
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Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.
Resumo:
Although various foot models were proposed for kinematics assessment using skin makers, no objective justification exists for the foot segmentations. This study proposed objective kinematic criteria to define which foot joints are relevant (dominant) in skin markers assessments. Among the studied joints, shank-hindfoot, hindfoot-midfoot and medial-lateral forefoot joints were found to have larger mobility than flexibility of their neighbour bonesets. The amplitude and pattern consistency of these joint angles confirmed their dominancy. Nevertheless, the consistency of the medial-lateral forefoot joint amplitude was lower. These three joints also showed acceptable sensibility to experimental errors which supported their dominancy. This study concluded that to be reliable for assessments using skin markers, the foot and ankle complex could be divided into shank, hindfoot, medial forefoot, lateral forefoot and toes. Kinematics of foot models with more segments must be more cautiously used.
Resumo:
OBJECTIVE: Imaging during a period of minimal myocardial motion is of paramount importance for coronary MR angiography (MRA). The objective of our study was to evaluate the utility of FREEZE, a custom-built automated tool for the identification of the period of minimal myocardial motion, in both a moving phantom at 1.5 T and 10 healthy adults (nine men, one woman; mean age, 24.9 years; age range, 21-32 years) at 3 T. CONCLUSION: Quantitative analysis of the moving phantom showed that dimension measurements approached those obtained in the static phantom when using FREEZE. In vitro, vessel sharpness, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were significantly improved when coronary MRA was performed during the software-prescribed period of minimal myocardial motion (p < 0.05). Consistent with these objective findings, image quality assessments by consensus review also improved significantly when using the automated prescription of the period of minimal myocardial motion. The use of FREEZE improves image quality of coronary MRA. Simultaneously, operator dependence can be minimized while the ease of use is improved.
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In a multicenter study a new, fully automated Roche Diagnostics Elecsys HBsAg II screening assay with improved sensitivity to HBsAg mutant detection was compared to well-established HBsAg tests: AxSYM HBsAg V2 (Abbott), Architect HBsAg (Abbott), Advia Centaur HBsAg (Bayer) Enzygnost HBsAg 5.0 (Dade-Behring), and Vitros Eci HBsAg (Ortho). A total of 16 seroconversion panels, samples of 60 HBsAg native mutants, and 31 HBsAg recombinant mutants, dilution series of NIBSC and PEI standards, 156 HBV positive samples comprising genotypes A to G, 686 preselected HBsAg positive samples from different stages of infection, 3,593 samples from daily routine, and 6,360 unselected blood donations were tested to evaluate the analytical and clinical sensitivity, the detection of mutants, and the specificity of the new assay. Elecsys HBsAg II showed a statistically significant better sensitivity in seroconversion panels to the compared tests. Fifty-seven out of 60 native mutants and all recombinant mutants were found positive. Among 156 HBV samples with different genotypes and 696 preselected HBsAg positive samples Elecsys HBsAg II achieved a sensitivity of 100%. The lower detection limit for NIBSC standard was calculated to be 0.025 IU/ml and for the PEI standards ad and ay it was <0.001 and <0.005 U/ml, respectively. Within 2,724 daily routine specimens and 6.360 unselected blood donations Elecsys HBsAg II showed a specificity of 99.97 and 99.88%, respectively. In conclusion the new Elecsys HBsAg II shows a high sensitivity for the detection of all stages of HBV infection and HBsAg mutants paired together with a high specificity in blood donors, daily routine samples, and potentially interfering sera.
Resumo:
This report documents work undertaken in the demonstration of a low-cost Automatic Weight and Classification System (AWACS). An AWACS procurement specification and details of the results of the project are also included. The intent of the project is to support and encourage transferring research knowledge to state and local agencies and manufacturers through field demonstrations. Presently available, Weigh-in-Motion and Classification Systems are typically too expensive to permit the wide deployment necessary to obtain representative vehicle data. Piezo electric technology has been used in the United Kingdom and Europe and is believed to be the basic element in a low-cost AWACS. Low-cost systems have been installed at two sites, one in Portland Cement Concrete (PCC) pavement in Iowa and the other in Asphaltic Cement Concrete (ACC) pavement in Minnesota to provide experience with both types of pavement. The systems provide axle weights, gross vehicle weight, axle spacing, vehicle classification, vehicle speed, vehicle count, and time of arrival. In addition, system self-calibration and a method to predict contact tire pressure is included in the system design. The study has shown that in the PCC pavement, the AWACS is capable of meeting the needs of state and federal highway agencies, producing accuracies comparable to many current commercial WIM devices. This is being achieved at a procurement cost of substantially less than currently available equipment. In the ACC pavement the accuracies were less than those observed in the PCC pavement which is concluded to result from a low pavement rigidity at this site. Further work is needed to assess the AWACS performance at a range of sites in ACC pavements.