888 resultados para Tree Crown Segmentation


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This paper presents automated segmentation of structuresin the Head and Neck (H\&N) region, using an activecontour-based joint registration and segmentation model.A new atlas selection strategy is also used. Segmentationis performed based on the dense deformation fieldcomputed from the registration of selected structures inthe atlas image that have distinct boundaries, onto thepatient's image. This approach results in robustsegmentation of the structures of interest, even in thepresence of tumors, or anatomical differences between theatlas and the patient image. For each patient, an atlasimage is selected from the available atlas-database,based on the similarity metric value, computed afterperforming an affine registration between each image inthe atlas-database and the patient's image. Unlike manyof the previous approaches in the literature, thesimilarity metric is not computed over the entire imageregion; rather, it is computed only in the regions ofsoft tissue structures to be segmented. Qualitative andquantitative evaluation of the results is presented.

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The Diagnosis and Recommendation System (DRIS) was applied to eucalypt trees (hybrids of Eucalyptus grandis x E. urophylla) with different ages and growing under different environmental conditions for three different clones. The basic data were obtained from 1,986 trees of commercial stands cultivated in the states of Espírito Santo and south Bahia, Brazil. The DRIS indices were calculated using the Beaufils' Range formula and grouped according to the Nutrient Application Potential Response method. The objective of this paper was to evaluate the N, P and Ca status in eucalypt trees, regarding the tree ages and genetic materials. The DRIS indices discriminated differences in the nutritional status of the trees, both in relation to age and the genetic materials (clones). The results indicated that the deficiency of N and Ca tended to decrease with tree age, whereas the P deficiency tended to increase. Furthermore, of the three evaluated clones, those numbered 00014 and 00034 showed opposite trends regarding to N, P, and Ca nutrition, and the clone numbered 00021, in general, presented the highest degree of unbalanced nutrition of N, P and Ca.

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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.

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Identifying Broadleaf Trees...A brochure on what type of broad leafs you look for when looking at trees in Iowa. Produced by the Iowa Department of Natural Resources.

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This document lists all trees and shrubs that are native to Iowa is their common name and scientific name. Along with height of maturity, growth rate uses and limitations.