78 citations
- Monash UniversityAU4 papers
- The University of MelbourneAU3 papers
- Defence Science and Technology GroupAU1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- Fuzhou UniversityCN1 paper
- Minghsin University of Science and TechnologyTW1 paper
- NYU Langone HealthUS1 paper
- Singapore University of Technology and DesignSG1 paper
- University Hospital of BernCH1 paper
- University of BernCH1 paper
- University of LausanneCH1 paper
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2021
Uncertainty guided semi-supervised segmentation of retinal layers in OCT images
Suman Sedai, Bhavna Antony, Ravneet Rai +5
Deep convolutional neural networks have shown outstanding performance in medical image segmentation tasks. The usual problem when training supervised deep learning methods is the l…
cs.CV2019
Informative sample generation using class aware generative adversarial networks for classification of chest Xrays
Behzad Bozorgtabar, Dwarikanath Mahapatra, Hendrik von Teng +4
Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem…
cs.CV2019★ 2 cited
Training Data Independent Image Registration With GANs Using Transfer Learning And Segmentation Information
Dwarikanath Mahapatra, Zongyuan Ge
Registration is an important task in automated medical image analysis. Although deep learning (DL) based image registration methods out perform time consuming conventional approach…