6. Sensitivity to noise and outliers
The presence of noise and outliers in images can significantly degrade registration quality. In some cases, it may be worthwhile to pre-process images to reduce noise levels using denoising methods, or to correct certain acquisition-related artifacts.
the origin of outliers may be related to acquisition artifacts or pathological changes in the imaged tissue, such as the appearance of lesions or the presence of a tumor.
The sensitivity of a registration method to noise and outliers is closely linked to the amount of information available to estimate the registration and the number of parameters to be estimated. The greater the number of degrees of freedom in the transformation, the more sensitive the parameter estimation is to noise and outliers. Conversely, in the case, for example, of...
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Sensitivity to noise and outliers
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