972 resultados para HEALTHCARE PLANNING
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The Iowa Department of Public Health Bureau of Family Health and the Child Health Specialty Clinics embarked on a five-year needs assessment in March 2008 with a daylong strategic planning session involving key administrative and staff personnel from both agencies. As part of the strategic planning, the participants began preparation of a comprehensive assessment to identify the need in Iowa for: preventive and primary care services for pregnant women, mothers, and infants; preventive and primary care services for children; and services for children and youth with special health care needs.
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PURPOSE: To compare 3 different flow targeted magnetization preparation strategies for coronary MR angiography (cMRA), which allow selective visualization of the vessel lumen. MATERIAL AND METHODS: The right coronary artery of 10 healthy subjects was investigated on a 1.5 Tesla MR system (Gyroscan ACS-NT, Philips Healthcare, Best, NL). A navigator-gated and ECG-triggered 3D radial steady-state free-precession (SSFP) cMRA sequence with 3 different magnetization preparation schemes was performed referred to as projection SSFP (selective labeling of the aorta, subtraction of 2 data sets), LoReIn SSFP (double-inversion preparation, selective labeling of the aorta, 1 data set), and inflow SSFP (inversion preparation, selective labeling of the coronary artery, 1 data set). Signal-to-noise ratio (SNR) of the coronary artery and aorta, contrast-to-noise ratio (CNR) between the coronary artery and epicardial fat, vessel length and vessel sharpness were analyzed. RESULTS: All cMRA sequences were successfully obtained in all subjects. Both projection SSFP and LoReIn SSFP allowed for selective visualization of the coronary arteries with excellent background suppression. Scan time was doubled in projection SSFP because of the need for subtraction of 2 data sets. In inflow SSFP, background suppression was limited to the tissue included in the inversion volume. Projection SSFP (SNR(coro): 25.6 +/- 12.1; SNR(ao): 26.1 +/- 16.8; CNR(coro-fat): 22.0 +/- 11.7) and inflow SSFP (SNR(coro): 27.9 +/- 5.4; SNR(ao): 37.4 +/- 9.2; CNR(coro-fat): 24.9 +/- 4.8) yielded significantly increased SNR and CNR compared with LoReIn SSFP (SNR(coro): 12.3 +/- 5.4; SNR(ao): 11.8 +/- 5.8; CNR(coro-fat): 9.8 +/- 5.5; P < 0.05 for both). Longest visible vessel length was found with projection SSFP (79.5 mm +/- 18.9; P < 0.05 vs. LoReIn) whereas vessel sharpness was best in inflow SSFP (68.2% +/- 4.5%; P < 0.05 vs. LoReIn). Consistently good image quality was achieved using inflow SSFP likely because of the simple planning procedure and short scanning time. CONCLUSION: Three flow targeted cMRA approaches are presented, which provide selective visualization of the coronary vessel lumen and in addition blood flow information without the need of contrast agent administration. Inflow SSFP yielded highest SNR, CNR and vessel sharpness and may prove useful as a fast and efficient approach for assessing proximal and mid vessel coronary blood flow, whereas requiring less planning skills than projection SSFP or LoReIn SSFP.
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Agency Performance Plan, Iowa Public Television
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This is volume 1 of the final report on the Comprehensive Plan for the City of Boone. Contained in this report are reproductions of the important maps and charts prepared in connection with this study.
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This is volume 2 of the final report on the Comprehensive Plan for the City of Boone. Contained in this report are reproductions of the important maps and charts prepared in connection with this study.
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This is volume 3 of the final report on the Comprehensive Plan for the City of Boone. Contained in this report are reproductions of the important maps and charts prepared in connection with this study.
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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.
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For radiotherapy treatment planning of retinoblastoma inchildhood, Computed Tomography (CT) represents thestandard method for tumor volume delineation, despitesome inherent limitations. CT scan is very useful inproviding information on physical density for dosecalculation and morphological volumetric information butpresents a low sensitivity in assessing the tumorviability. On the other hand, 3D ultrasound (US) allows ahigh accurate definition of the tumor volume thanks toits high spatial resolution but it is not currentlyintegrated in the treatment planning but used only fordiagnosis and follow-up. Our ultimate goal is anautomatic segmentation of gross tumor volume (GTV) in the3D US, the segmentation of the organs at risk (OAR) inthe CT and the registration of both. In this paper, wepresent some preliminary results in this direction. Wepresent 3D active contour-based segmentation of the eyeball and the lens in CT images; the presented approachincorporates the prior knowledge of the anatomy by usinga 3D geometrical eye model. The automated segmentationresults are validated by comparing with manualsegmentations. Then, for the fusion of 3D CT and USimages, we present two approaches: (i) landmark-basedtransformation, and (ii) object-based transformation thatmakes use of eye ball contour information on CT and USimages.