Factors influencing image quality

The processing errors are due to various factors as the orientation and number of views that influence the quality of the approximation. A reduced number of views decrease the amount of errors but increase image composition distortions at the edges of each image. The filtering processes and the noise reduction of digitized geometries have influence in the subsequent approximations. 

Image quality in CT is determined both by spatial resolution and contrast. It is the tube current (mA) that primarily affects spatial resolution, whilst the peak tube potential (kVp) affects both spatial and contrast resolution. Other factors influencing spatial resolution - the ability to observe small details - include in the imaging plane the collimation (in SDCT) - or section collimation (in MDCT) and the focal spot size of the tube. The slice (section) thickness and the choice of pitch influence spatial resolution along the Z-(long) axis of the patient - thinner slices and a lower pitch leading to an improvement in spatial resolution (Huda et al. 2002). 

In the multiset analysis, spectral consistency and, therefore, compound identity are ensured because of the architecture of the multiset (with a single matrix), and distribution maps are better defined. The deficient quality of the results obtained by individual single image analysis in this example is due to two different factors (a) not all sample constituents are sufficiently represented in all emulsion layers and (b) the quality of the Raman signal (signal-to-noise ratio) decreases as depth increases. These problems are solved with multiset analysis because of the complementary composition information from the different images and the better signal-to-noise ratio of top emulsion layers that influence the quality of the overall multiset structure results. 

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