3 resultados para Calibration phantom
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
Objective: To compare two methods of respiratory inductive plethysmography (RIP) calibration in three different positions. Methods: We evaluated 28 healthy subjects (18 women and 10 men), with a mean age of 25.4 +/- 3.9 years. For all of the subjects, isovolume maneuver calibration (ISOCAL) and qualitative diagnostic calibration (QDC) were used in the orthostatic, sitting, and supine positions. In order to evaluate the concordance between the two calibration methods, we used ANOVA and Bland-Altman plots. Results: The values of the constant of proportionality (X) were significantly different between ISOCAL and QDC in the three positions evaluated: 1.6 +/- 0.5 vs. 2.0 +/- 1.2, in the supine position, 2.5 +/- 0.8 vs. 0.6 +/- 0.3 in the sitting position, and 2.0 +/- 0.8 vs. 0.6 +/- 0.3 in the orthostatic position (p < 0.05 for all). Conclusions: Our results suggest that QDC is an inaccurate method for the calibration of RIP. The K values obtained with ISOCAL reveal that RIP should be calibrated for each position evaluated.
Resumo:
The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.
Resumo:
The strain image contrast of some in vivo breast lesions changes with increasing applied load. This change is attributed to differences in the nonlinear elastic properties of the constituent tissues suggesting some potential to help classify breast diseases by their nonlinear elastic properties. A phantom with inclusions and long-term stability is desired to serve as a test bed for nonlinear elasticity imaging method development, testing, etc. This study reports a phantom designed to investigate nonlinear elastic properties with ultrasound elastographic techniques. The phantom contains four spherical inclusions and was manufactured from a mixture of gelatin, agar and oil. The phantom background and each of the inclusions have distinct Young's modulus and nonlinear mechanical behavior. This phantom was subjected to large deformations (up to 20%) while scanning with ultrasound, and changes in strain image contrast and contrast-to-noise ratio between inclusion and background, as a function of applied deformation, were investigated. The changes in contrast over a large deformation range predicted by the finite element analysis (FEA) were consistent with those experimentally observed. Therefore, the paper reports a procedure for making phantoms with predictable nonlinear behavior, based on independent measurements of the constituent materials, and shows that the resulting strain images (e. g., strain contrast) agree with that predicted with nonlinear FEA.