How do Sabine Van Huffel's methods apply to medical imaging?
In medical imaging, data acquisition is often subject to noise and uncertainties. My work on total least squares provides a robust framework for analyzing this type of data. For example, in reconstructing images or extracting meaningful features, TLS can account for errors in both the observed signals and the underlying physical models. This leads to more accurate diagnoses and better understanding of physiological processes, particularly in areas like MRI and CT scans.
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