Texture analysis combined with attention mapping has the potential to identify the position of pathology normally not visible in MR images by exploiting inter-pixel relationships in magnetic resonance (MR) images. However, as pathology can influence adjacent tissue, the features used to identify the position of the pathology have to be selected with care. Here we present an easily implemented method that efficiently selects texture features that are only sensitive to the pathology and can improve the localization of pathology even when not visible in MR images.
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