2 resultados para computed tomography images

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We report on the construction of anatomically realistic three-dimensional in-silico breast phantoms with adjustable sizes, shapes and morphologic features. The concept of multiscale spatial resolution is implemented for generating breast tissue images from multiple modalities. Breast epidermal boundary and subcutaneous fat layer is generated by fitting an ellipsoid and 2nd degree polynomials to reconstructive surgical data and ultrasound imaging data. Intraglandular fat is simulated by randomly distributing and orienting adipose ellipsoids within a fibrous region immediately within the dermal layer. Cooper’s ligaments are simulated as fibrous ellipsoidal shells distributed within the subcutaneous fat layer. Individual ductal lobes are simulated following a random binary tree model which is generated based upon probabilistic branching conditions described by ramification matrices, as originally proposed by Bakic et al [3, 4]. The complete ductal structure of the breast is simulated from multiple lobes that extend from the base of the nipple and branch towards the chest wall. As lobe branching progresses, branches are reduced in height and radius and terminal branches are capped with spherical lobular clusters. Biophysical parameters are mapped onto the complete anatomical model and synthetic multimodal images (Mammography, Ultrasound, CT) are generated for phantoms of different adipose percentages (40%, 50%, 60%, and 70%) and are analytically compared with clinical examples. Results demonstrate that the in-silico breast phantom has applications in imaging performance evaluation and, specifically, great utility for solving image registration issues in multimodality imaging.

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Open-cell metal foams show promise as an emerging novel material for heat exchanger applications. The high surface-area-to-volume ratio suggests increased compactness and decrease in weight of heat exchanger designs. However, the metal foam structure appears conducive to condensate retention, which would degenerate heat transfer performance. This research investigates the condensate retention behavior of aluminum open-cell metal foams through the use of static dip tests and geometrical classification via X-ray Micro-Computed Tomography. Aluminum open-cell metal foam samples of 5, 10, 20, and 40 pores per inch (PPI), all having a void fraction greater than 90%, were included in this investigation. In order to model the condensate retention behavior of metal foams, a clearer understanding of the geometry was required. After exploring the ideal geometries presented in the open literature, X-ray Micro-Computed Tomography was employed to classify the actual geometry of the metal foam samples. The images obtained were analyzed using specialized software from which geometric information including strut length and pore shapes were extracted. The results discerned a high variability in ligament length, as well as features supporting the ideal geometry known as the Weaire-Phelan unit cell. The static dip tests consisted of submerging the metal foam samples in a liquid, then allowing gravity-induced drainage until steady-state was reached and the liquid remaining in the metal foam sample was measured. Three different liquids, water, ethylene glycol, and 91% isopropyl alcohol, were employed. The behaviors of untreated samples were compared to samples subjected to a Beomite surface treatment process, and no significant differences in retention behavior were discovered. The dip test results revealed two distinct regions of condensate retention, each holding approximately half of the total liquid retained by the sample. As expected, condensate retention increased as the pores sizes decreased. A model based on surface tension was developed to predict the condensate retention in the metal foam samples and verified using a regular mesh. Applying the model to both the ideal and actual metal foam geometries showed good agreement with the dip test results in this study.