HIGHLIGHTS
SUMMARY
M of the field they scatter, are worth mentioning. The typical outcome of qualitative imaging methods is a continuous map of an indicator function, which usually takes on large values where the target is supposed to be located and low values elsewhere. While this can be sufficient to provide qualitative visual information about the target, it does not provide a clear indication of the actual morphological properties. This approach consists in enhancing qualitative imaging with an automated classification, based on deep learning (DL), to enable a userindependent procedure. For instance, direct learning methods provide . . .
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