Tibor Auer
Radiology, Nuclear Medicine and Imaging · 2016–2017
A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Radiology, Nuclear Medicine and Imaging — 22 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Tibor Auer trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- John Ashburner (in Radiology, Nuclear Medicine and Imaging)
Papers from Tibor Auer's perspective
Ordered by how strongly the researchers Tibor Auer trusts endorse each paper. Same corpus, a different order for every researcher.
- An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest (NeuroImage)
- A fast diffeomorphic image registration algorithm (NeuroImage)
- Advances in functional and structural MR image analysis and implementation as FSL.
- The Minimal Preprocessing Pipelines for the Human Connectome Project (NeuroImage)
- Performing Label-Fusion-Based Segmentation Using Multiple Automatically Generated Templates (Human Brain Mapping)
- Comparison of JSON and XML Data Interchange Formats: A Case Study (ISCA International Conference on Computer Applications in Industry and Engineering)
- A whole brain fMRI atlas generated via spatially constrained spectral clustering
- Open is Not Enough. Let's Take the Next Step: An Integrated, Community-Driven Computing Platform for Neuroscience
- Towards Automated Analysis of Connectomes: The Configurable Pipeline for the Analysis of Connectomes (C-PAC)
- Applications of the signal space separation method (IEEE Transactions on Signal Processing)
Their papers
- The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments (2016) — 1,663 citations
- The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample (2017) — 729 citations
- BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods (2016) — 311 citations