Camino: Open-Source Diffusion-MRI Reconstruction and Processing
By P. Cook, Y. Bai, S. Nedjati-Gilani, K. Seunarine, M. Hall, G. Parker, Daniel C. Alexander. 2006
636 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/6de9805ed125e5479e4c58f82472aac2ab6d85df
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Axel Thielscher
- Jelle Veraart
- Jacques-Donald Tournier
- Mirko Windhoff
- Alexander Leemans
- Jan Sijbers
- Alexander Opitz
- Hui Zhang
Citations in the corpus
- A hitchhiker's guide to diffusion tensor imaging (2012, unknown): “Camino (Cook et al., 2006) http://web4.”
- NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain (2012, methodology): “(2007) and implemented in Camino (Cook et al., 2006), which ensures that the orientations within each subset are as uniformly distributed as possible.”
- Evidence for Segregated and Integrative Connectivity Patterns in the Human Basal Ganglia (2008, methodology): “…was performed in subject-specific native space using the previously described probabilistic index of connectivity (PICo) algorithm (Parker and Alexander, 2003, 2005) implemented in the freely available Camino software package (http://www.cs.ucl.ac.uk/research/medic/camino/) (Cook et al., 2006).”
- Orientationally invariant indices of axon diameter and density from diffusion MRI (2010, methodology): “The diffusion simulation system in Hall and Alexander (2009), which is freely available in the Camino toolkit (Cook et al., 2006; http://www.camino.org.uk), generates synthetic diffusion MRI data by simulating random walks of molecules within restricting geometries.”
- Compartment models of the diffusion MR signal in brain white matter: A taxonomy and comparison (2012, unknown): “We do not list full initialization details for all models here, but more information is in Panagiotaki (2011) or in the implementation in the open source Camino toolkit (Cook et al., 2006).”
- Dipy, a library for the analysis of diffusion MRI data (2014, background): “(Cook et al., 2006) and Matlab: ExploreDTI (Leemans et al., 2009), AFQ (Yeatman et al., 2012) and others.”
- Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls (2013, methodology): “The latter strategy was adopted by software packages such as Camino (Cook et al., 2006) and Slicer v4.”
- How the brain tissue shapes the electric field induced by transcranial magnetic stimulation (2011, methodology): “The tracking used the tensor data and was based on the streamline approach implemented in CAMINO (Cook et al., 2006).”