Sentence examples for variation of tissue from inspiring English sources
Dynamic magnetic resonance imaging (MRI) acquires a sequence of images for the visualization of the temporal variation of tissue or organs.
This method with resonance frequency analysis (RFA) technology measures the amount of variation of tissue stiffness around the implant and gives relevant information about the bone-implant interface [6].
Recently there has been encouraging progress in neonatal cerebral tissue segmentation using probabilistic atlases that exploit anatomical knowledge [24] [27] and by using regional expectation-maximization algorithm to account for spatial variation of tissue intensity [28].
However, a previous study showed a low variation of tissue C∶N∶P stoichiometry among mussels collected from one sampling site; suggesting a number of 15 individuals of mussels would provide a reasonable value of C∶N∶P ratio for mussels stoichiometry [7].
The variation of tissue thickness can be used to reflect the deformation degree of tissue structure qualitatively.
Within a normalization group, the variation of tissue type was thus minimized although the expression profiles were nevertheless obtained from different microarray studies.
In the present study, influence of mRNA secondary structural stability on codon usage variation of tissue-specific genes might be the consequence of favoring non-optimal codons in lowly expressed tissue-specific genes.
With physical variations of tissue tensile strength, anatomic differences, and neurophysiologic considerations, such threshold designation is not possible.
To test whether the variations of tissue hemoglobin concentration (∆THb) measured by the FORE-SIGHTTM cerebral oximeter can accurately detect changes in arterial hemoglobin concentration (∆AHb) before, during, and after cardiopulmonary bypass.
Near-infrared spectroscopy (NIRS) has been used to quantify sepsis-induced metabolic alterations by measuring variations of tissue oxygen saturation (StO2) during a vascular occlusion test (VOT).
Within the selected patient cohort, the distinct and consistent morphology of CRC tumour necessitated the generation of only a few variations of tissue classifiers for different sets of tumour samples.
