activity
20152021
most citedA large annotated medical image dataset for the development and evaluation of segmentation algorithms

718 citations · 930 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CE202131 cited

Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs

Dan Rosenbaum, Marta Garnelo, Michal Zielinski +10

Cryo-electron microscopy (cryo-EM) has revolutionized experimental protein structure determination. Despite advances in high resolution reconstruction, a majority of cryo-EM experi…

cs.LG202052 cited

Contrastive Training for Improved Out-of-Distribution Detection

Jim Winkens, Rudy Bunel, Abhijit Guha Roy +10

Reliable detection of out-of-distribution (OOD) inputs is increasingly understood to be a precondition for deployment of machine learning systems. This paper proposes and investiga…

cs.CV201927 cited

A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities

Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein +5

Medical imaging only indirectly measures the molecular identity of the tissue within each voxel, which often produces only ambiguous image evidence for target measures of interest,…

cs.CV2019718 cited

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Amber L. Simpson, Michela Antonelli, Spyridon Bakas +21

Semantic segmentation of medical images aims to associate a pixel with a label in a medical image without human initialization. The success of semantic segmentation algorithms is c…

cs.CV2018

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch +26

Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manua…

cs.CV2018

A Probabilistic U-Net for Segmentation of Ambiguous Images

Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer +6

Many real-world vision problems suffer from inherent ambiguities. In clinical applications for example, it might not be clear from a CT scan alone which particular region is cancer…