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The medical image fusion combines two or more modalities into a single viewwhile medical image translation synthesizes new images and assists in dataaugmentation. Together, these methods help in faster diagnosis of high grademalignant gliomas. However, they might be untrustworthy due to whichneurosurgeons demand a robust visualisation tool to verify the reliability ofthe fusion and translation results before they make pre-operative surgicaldecisions. In this paper, we propose a novel approach to compute a confidenceheat map between the source-target image pair by estimating the informationtransfer from the source to the target image using the joint probabilitydistribution of the two images. We evaluate several fusion and translationmethods using our visualisation procedure and showcase its robustness inenabling neurosurgeons to make finer clinical decisions.

Visualisation of Medical Image Fusion and Translation for Accurate Diagnosis of High Grade Gliomas