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Suaiba Amina Salahuddin, UiT, PhD-student i Visual Intelligence, UiT Machine Learning Group.
This presentation will start with a brief background on my educational history and experience. I will then present some preliminary work on segmentation of medical images leveraging so-called few-shot learning, which in this case is based on learning foreground and prototypes which form the basis for pixel classification. The new idea is to incorporate a self-guidance module in the generation of prototypes based on initial errors, to achieve boosted segmentation with primary and auxiliary prototypes. The proposed framework´s performance on cardiac MR and liver CT segmentation will be discussed. The presentation ends with an outlook on potential future research focus.