107 citations
- Imperial College LondonGB7 papers
- NIHR Imperial Biomedical Research CentreGB3 papers
- Technical University of MunichDE2 papers
- TUM KlinikumDE2 papers
- Charles UniversityCZ1 paper
- Consejo Nacional de Investigaciones Científicas y TécnicasAR1 paper
- Erasmus MCNL1 paper
- Erasmus University RotterdamNL1 paper
- Friedrich-Alexander-Universität Erlangen-NürnbergDE1 paper
- Graz University of TechnologyAT1 paper
- Indian Institute of Technology MadrasIN1 paper
- Institute of Mathematical StatisticsUS1 paper
15 papers
Most totally real fields do not have universal forms or Northcott property
Nicolas Daans, Vitezslav Kala, Siu Hang Man +2
We show that, in the space of all totally real fields equipped with the constructible topology, the set of fields that admit a universal quadratic form, or have the Northcott prope…
Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling
Philip Müller, Felix Meissen, Georgios Kaissis +1
Weakly supervised object detection (WSup-OD) increases the usefulness and interpretability of image classification algorithms without requiring additional supervision. The successe…
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art
Ioannis Lagogiannis, Felix Meissen, Georgios Kaissis +1
Deep unsupervised approaches are gathering increased attention for applications such as pathology detection and segmentation in medical images since they promise to alleviate the n…
Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging
Richard Osuala, Kaisar Kushibar, Lidia Garrucho +6
Despite technological and medical advances, the detection, interpretation, and treatment of cancer based on imaging data continue to pose significant challenges. These include inte…
Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net
Tianrui Liu, Qingjie Meng, Jun-Jie Huang +3
Intelligent video summarization algorithms allow to quickly convey the most relevant information in videos through the identification of the most essential and explanatory content…
Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders
Agostina J Larrazabal, César Martínez, Ben Glocker +1
We introduce Post-DAE, a post-processing method based on denoising autoencoders (DAE) to improve the anatomical plausibility of arbitrary biomedical image segmentation algorithms.…