Vertical Bone Measurements From Cone Beam Computed Tomography Images Using Different Software Packages.

This article aimed at comparing the accuracy of linear measurement tools of different commercial software packages. Eight fully edentulous dry mandibles were selected for this study. Incisor, canine, premolar, first molar and second molar regions were selected. Cone beam computed tomography (CBCT) images were obtained with i-CAT Next Generation. Linear bone measurements were performed by one observer on the cross-sectional images using three different software packages: XoranCat®, OnDemand3D® and KDIS3D®, all able to assess DICOM images. In addition, 25% of the sample was reevaluated for the purpose of reproducibility. The mandibles were sectioned to obtain the gold standard for each region. Intraclass coefficients (ICC) were calculated to examine the agreement between the two periods of evaluation; the one-way analysis of variance performed with the post-hoc Dunnett test was used to compare each of the software-derived measurements with the gold standard. The ICC values were excellent for all software packages. The least difference between the software-derived measurements and the gold standard was obtained with the OnDemand3D and KDIS3D (-0.11 and -0.14 mm, respectively), and the greatest, with the XoranCAT (+0.25 mm). However, there was no statistical significant difference between the measurements obtained with the different software packages and the gold standard (p> 0.05). In conclusion, linear bone measurements were not influenced by the software package used to reconstruct the image from CBCT DICOM data.

Modelos de regressão lineares para estimativa de produtividade da soja no oeste do Paraná, utilizando dados espectrais

The main objective of this work was to evaluate the linear regression between spectral response and soybean yield in regional scale. In this study were monitored 36 municipalities from the west region of the states of Parana using five images of Landsat 5/TM during 2004/05 season. The spectral response was converted in physical values, apparent and surface reflectances, by radiometric transformation and atmospheric corrections and both used to calculate NDVI and GVI vegetation indices. Those ones were compared by multiple and simple regression with government official yield values (IBGE). Diagnostic processing method to identify influents values or collinearity was applied to the data too. The results showed that the mean surface reflectance value from all images was more correlated with yield than individual dates. Further, the multiple regressions using all dates and both vegetation indices gave better results than simple regression.