335 citations · 583 across the 23 of their papers we have counts for
5 papers · 1 filter
Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016
Sarah Parisot, Jonathan Passerat-Palmbach, Markus D. Schirmer +1
Understanding brain connectivity in a network-theoretic context has shown much promise in recent years. This type of analysis identifies brain organisational principles, bringing a…
Comparison of Brain Networks with Unknown Correspondences
Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach +1
Graph theory has drawn a lot of attention in the field of Neuroscience during the last decade, mainly due to the abundance of tools that it provides to explore the interactions of…
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks
Martin Rajchl, Matthew C. H. Lee, Ozan Oktay +8
In this paper, we propose DeepCut, a method to obtain pixelwise object segmentations given an image dataset labelled with bounding box annotations. It extends the approach of the w…
Learning under Distributed Weak Supervision
Martin Rajchl, Matthew C. H. Lee, Franklin Schrans +7
The availability of training data for supervision is a frequently encountered bottleneck of medical image analysis methods. While typically established by a clinical expert rater,…
Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies
Lisa M. Koch, Martin Rajchl, Wenjia Bai +5
Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability…