Publications

GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images.

Published in Arxiv Preprint., 2021

In this work, we explored the use on Normalizing flows in learning disentangled representations of Brain MRI scans.

Sankar, A., Keicher, M., Eisawy, R., Parida, A., Pfister, F., Kim, S. T., & Navab, N. (2021). GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images. arXiv preprint arXiv:2103.10868. https://arxiv.org/abs/2103.10868

Train, Learn, Expand, Repeat.

Published in ICLR 2020 workshop on AI for Affordable Healthcare., 2020

A recursive training strategy to perform the task of semantic segmentation given only very few training samples with pixel-level annotations.

Parida, A., Sankar, A., Eisawy, R., Finck, T., Wiestler, B., Pfister, F., & Moosbauer, J. (2020). Train, Learn, Expand, Repeat. arXiv preprint arXiv:2003.08469. https://arxiv.org/pdf/2003.08469