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eess.IV2024
Exploiting XAI maps to improve MS lesion segmentation and detection in MRI
Federico Spagnolo, Nataliia Molchanova, Mario Ocampo Pineda +5
To date, several methods have been developed to explain deep learning algorithms for classification tasks. Recently, an adaptation of two of such methods has been proposed to gener…
eess.IV2024★ 3 cited
Instance-level quantitative saliency in multiple sclerosis lesion segmentation
Federico Spagnolo, Nataliia Molchanova, Meritxell Bach Cuadra +5
Explainable artificial intelligence (XAI) methods have been proposed to interpret model decisions in classification and, more recently, in semantic segmentation. However, instance-…