6 citations · 10 across the 2 of their papers we have counts for
5 papers
Information-based Disentangled Representation Learning for Unsupervised MR Harmonization
Lianrui Zuo, Blake E. Dewey, Aaron Carass +4
Accuracy and consistency are two key factors in computer-assisted magnetic resonance (MR) image analysis. However, contrast variation from site to site caused by lack of standardiz…
Self domain adapted network
Yufan He, Aaron Carass, Lianrui Zuo +2
Domain shift is a major problem for deploying deep networks in clinical practice. Network performance drops significantly with (target) images obtained differently than its (source…
Validating uncertainty in medical image translation
Jacob C. Reinhold, Yufan He, Shizhong Han +5
Medical images are increasingly used as input to deep neural networks to produce quantitative values that aid researchers and clinicians. However, standard deep neural networks do…
Finding novelty with uncertainty
Jacob C. Reinhold, Yufan He, Shizhong Han +5
Medical images are often used to detect and characterize pathology and disease; however, automatically identifying and segmenting pathology in medical images is challenging because…
Topology guaranteed segmentation of the human retina from OCT using convolutional neural networks
Yufan He, Aaron Carass, Bruno M. Jedynak +4
Optical coherence tomography (OCT) is a noninvasive imaging modality which can be used to obtain depth images of the retina. The changing layer thicknesses can thus be quantified b…