31 citations · 60 across the 5 of their papers we have counts for
4 papers · 1 filter
A unified representation network for segmentation with missing modalities
Kenneth Lau, Jonas Adler, Jens Sjölund
Over the last few years machine learning has demonstrated groundbreaking results in many areas of medical image analysis, including segmentation. A key assumption, however, is that…
Banach Wasserstein GAN
Jonas Adler, Sebastian Lunz
Wasserstein Generative Adversarial Networks (WGANs) can be used to generate realistic samples from complicated image distributions. The Wasserstein metric used in WGANs is based on…
A modified fuzzy C means algorithm for shading correction in craniofacial CBCT images
Awais Ashfaq, Jonas Adler
CBCT images suffer from acute shading artifacts primarily due to scatter. Numerous image-domain correction algorithms have been proposed in the literature that use patient-specific…
Learning to solve inverse problems using Wasserstein loss
Jonas Adler, Axel Ringh, Ozan Öktem +1
We propose using the Wasserstein loss for training in inverse problems. In particular, we consider a learned primal-dual reconstruction scheme for ill-posed inverse problems using…