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hello my name is severio vadakino and today iamp;#39;ll be presenting had net a hierarchical adversarial knowledge solution network for improved enhanced tumor segmentation without post-contrast images a work developed by myself and several colleagues at mcgill university under the supervision of professors tal arbel and james j clark it is well known the inclusion of different mri sequences greatly improves the performance of automatic tumor or lesion segmentation networks in particular the presence of contrast enhanced t1 weighted mri has been shown to play a crucial role in the automatic segmentation of enhancing tumors and lesions however acquiring t1c images involves injecting a patient with a contrast agent like gadolinium a process that is invasive and that is no longer thought to be safe for patients unfortunately without these post-contrast images the segmentation of these enhancing tumors and lesions becomes extremely difficult despite this in this work we focus on attemptin