research
∙
05/29/2019
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
Diagnosis and treatment guidance are aided by detecting relevant biomark...
share
research
∙
01/24/2019
Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation
Optical coherence tomography (OCT) has become the most important imaging...
research
∙
01/23/2019
U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans
In this paper, we introduce a Bayesian deep learning based model for seg...
research
∙
10/31/2018
Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data
The identification and quantification of markers in medical images is cr...
research
∙
05/08/2018
Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images
The automatic detection of disease related entities in retinal imaging d...
research
∙
03/17/2017
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
Obtaining models that capture imaging markers relevant for disease progr...
research
∙
12/02/2016
