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Therefore, the primary objective of this study was to explore the performance of various commonly used (semi- automatic VOI methodsemi- automaticimaging parameters, i.e. image reconstruction settings and filtering, image noise leVOIs, and tumethodsaracteristics.
3. Lacunes and recent small subcortical infarcts are other terms that preferably should be used depending on imaging manifestations.
Nonetheless, each individual subtomogram does contain some high-resolution information, which, upon averaging with other ostensibly identical particles, can be recovered to yield structures at much higher resolution, depending on imaging conditions.
The overall signal amplitude of extracted spectra varied depending on imaging depth; however, the shapes of the excitation spectra were quite consistent.
The staining employed gave a glycocalyx height of 100-400 nm, depending on imaging modality.
In brief, the symmetric autocorrelation function was calculated and smoothed using a Gaussian kernel with a variance depending on imaging frequency.
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The positions of the intensity extrema within the image depend on imaging conditions, orientation and sample thickness, hence they do not necessarily coincide with the atomic positions.
They showed that the performance of a delineation method depends on imaging parameters (i.e. reconstruction settings, image noise level, tumour characteristics, contrast) and you need to choose the suitable delineation method accordingly to get the optimum results.
However, if there is no indication for that in the first place, the diagnosis will have to depend on imaging including chest x-rays, ultrasound, magnetic resonance imaging, or computed tomography (CT).
It is worth noting that the influx constant depends on imaging time, the type of tissue, and the type of tracer used, so preceding validation studies should be performed prior to implementation of the non-equilibrium data to the fitting process.
Diagnosis of breast cancer depends on imaging, biomarkers and pathology.
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