1000 resultados para statistical emission


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Purpose: Although several approaches have been already used to reduce radiation dose, CT doses are still among the high doses in radio-diagnostic. Recently, General Electric introduced a new imaging reconstruction technique, adaptive statistical iterative reconstruction (ASIR), allows to taking into account the statistical fluctuation of noise. The benefits of ASIR method were assessed through classic metrics and the evaluations of cardiac structures by radiologists. Methods and materials: A 64-row CT (MDCT) was employed. Catphan600 phantom acquisitions and 10 routine-dose CT examinations performed at 80 kVp were reconstructed with FBP and with 50% of ASIR. Six radiologists then assessed the visibility of main cardiac structures using the visual grading analysis (VGA) method. Results: On phantoms, for a constant value of SD (25 HU), CTDIvol is divided by 2 (8 mGy to 4 mGy) when 50% of ASIR is used. At constant CTDIvol, MTF medium frequencies were also significantly improved. First results indicated that clinical images reconstructed with ASIR had a better overall image quality compared with conventional reconstruction. This means that at constant image quality the radiation dose can be strongly reduced. Conclusion: The first results of this study shown that the ASIR method improves the image quality on phantoms by decreasing noise and improving resolution with respect to the classical one. Moreover, the benefit obtained is higher at lower doses. In clinical environment, a dose reduction can still be expected on 80 kVp low dose pediatric protocols using 50% of iterative reconstruction. Best ASIR percentage as a function of cardiac structures and detailed protocols will be presented for cardiac examinations.

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This supplementary project has been undertaken as an effort to continue work previously completed in the Pooled Fund Study of Premature Concrete Pavement Deterioration. As such, it shares the objective of "Identifying the variables that are present in those pavements exhibiting premature deterioration," by collecting additional data and performing statistical analysis of those data. The approach and philosophy of this work are identical to that followed in the above project, and the Pooled Fund Study Final Report provides a detailed description of this process. This project has involved the collection of data for additional sites in the state of Iowa. These sites have then been added to sites collected in the original study, and statistical analysis has been performed on the entire set. It is hoped that this will have two major effects. First, using data from only one state allows for the analysis of a larger set of independent variables with a greater degree of commonality than was possible in the multi-state study, since the data are not limited by state to state differences in data collection and retention. Second, more data on additional sites will increase the degrees of freedom in the model and hopefully add confidence to the results.

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Preoperative imaging for resection of chest wall malignancies is generally performed by computed tomography (CT). We evaluated the role of (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in planning full-thickness chest wall resections for malignancies. We retrospectively included 18 consecutive patients operated from 2004 to 2006 at our institution. Tumor extent was measured by CT and PET, using the two largest perpendicular tumor extensions in the chest wall plane to compute the tumor surface assuming an elliptical shape. Imaging measurements were compared to histopathology assessment of tumor borders. CT assessment consistently overestimated the tumor size as compared to PET (+64% vs. +1%, P<0.001). Moreover, PET was significantly better than CT at defining the size of lesions >24 cm(2) corresponding to a mean diameter >5.5 cm or an ellipse of >4 cm x 7.6 cm (positive predictive value 80% vs. 44% and specificity 93% vs. 64%, respectively). Metabolic PET imaging was superior to CT for defining the extent of chest wall tumors, particularly for tumors with a diameter >5.5 cm. PET can complement CT in planning full-thickness chest wall resection for malignancies, but its true value remains to be determined in larger, prospective studies.

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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.

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The objective of this study was to establish critical values of the N indices, namely soil-plant analysis development (SPAD), petiole sap N-NO3 and organic N in the tomato leaf adjacent to the first cluster (LAC), under soil and nutrient solution conditions, determined by different statistical approaches. Two experiments were conducted in randomized complete block design with four repli-cations. Tomato plants were grown in soil, in 3 L pot, with five N rates (0, 100, 200, 400 and 800 mg kg-1) and in solution at N rates of 0, 4, 8, 12 and 16 mmol L-1. Experiments in nutrient solution and soil were finished at thirty seven and forty two days after transplanting, respectively. At those times, SPAD index and petiole sap N-NO3 were evaluated in the LAC. Then, plants were harvested, separated in leaves and stem, dried at 70ºC, ground and weighted. The organic N was determined in LAC dry matter. Three statistical procedures were used to calculate critical N values. There were accentuated discrepancies for critical values of N indices obtained with plants grown in soil and nutrient solution as well as for different statistical procedures. Critical values of nitrogen indices at all situations are presented.

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