1 code implementation • 12 Jan 2024 • Eytan Kats, Jochen G. Hirsch, Mattias P. Heinrich
This paper demonstrates a self-supervised framework for learning voxel-wise coarse-to-fine representations tailored for dense downstream tasks.
no code implementations • 26 Oct 2019 • Eytan Kats, Jacob Goldberger, Hayit Greenspan
Supervised machine learning algorithms, especially in the medical domain, are affected by considerable ambiguity in expert markings.
no code implementations • 26 Jan 2019 • Eytan Kats, Jacob Goldberger, Hayit Greenspan
Detection and segmentation of MS lesions is a complex task largely due to the extreme unbalanced data, with very small number of lesion pixels that can be used for training.