The new correction method is a simple tool for excluding intrinsic influences on the enhancement of lesions. Quantitative enhancement evaluation with this method of the influence of intrinsic factors enables accurate differentiation between renal clear cell carcinoma and renal papillary carcinoma.
Triphasic helical CT combined with quantitative evaluation of liver lesions offers the possibility of detecting differences in liver lesions that are visually similar on CT. The attenuation and relative enhancement in the arterial phase show significant differences that make accurate differentiation between focal nodular hyperplasia and hepatocellular adenoma possible.
In this study laser scanner canopy height metrics data from the laser scanner Toposys-1 were investigated to derive forest attributes such as timber volume, tree height, and crown area coverage for the use in forest inventories. Investigations were based both on single tree information from crown segmentation and stand-wise assessments. While the statistical stand-wise approach only utilizes mean values for stand areas, the single tree classification approach makes use of the full potential of the high resolution laser scanner data. Forest inventory parameters were classified on the base of single trees or small groups of trees using digital image processing methods such as segmentation and data filtering. Stand-wise forest inventory data and single tree information were regressed against laser-derived features. Accuracy for additional stand parameters depends on crown closure and tree species. The obtained accuracy for tree heights from the approaches described is within the accuracy of conventional field based measurements. Further, it was investigated in how far laser scanner data is appropriate to assess timber volume. The described approaches can be used operationally for stand-wise forest inventories. Especially the single tree approach can be used instead of time-and cost-intensive field work in cases when full enumeration is required.
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