UCL Camino Diffusion MRI Toolkit. Camino is an open-source software toolkit for diffusion MRI processing. The toolkit implements standard techniques, such as diffusion tensor fitting, mapping fractional anisotropy and mean diffusivity, deterministic and probabilistic tractography. It also contains more specialized and cutting-edge techniques, such as Monte-Carlo diffusion simulation, multi-fibre and HARDI reconstruction techniques, multi-fibre PICo, compartment models, and axon density and diameter estimation.

References in zbMATH (referenced in 20 articles )

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  1. Celledoni, E.; Ehrhardt, M. J.; Etmann, C.; McLachlan, R. I.; Owren, B.; Schonlieb, C.-B.; Sherry, F.: Structure-preserving deep learning (2021)
  2. Corbin, Gregor; Klar, Axel; Surulescu, Christina; Engwer, Christian; Wenske, Michael; Nieto, Juanjo; Soler, Juan: Modeling glioma invasion with anisotropy- and hypoxia-triggered motility enhancement: from subcellular dynamics to macroscopic PDEs with multiple taxis (2021)
  3. Diepeveen, Willem; Lellmann, Jan: An inexact semismooth Newton method on Riemannian manifolds with application to duality-based total variation denoising (2021)
  4. Engwer, Christian; Wenske, Michael: Estimating the extent of glioblastoma invasion. Approximate stationalization of anisotropic advection-diffusion-reaction equations in the context of glioblastoma invasion (2021)
  5. Baust, Maximilian; Weinmann, Andreas: Manifold-valued data in medical imaging applications (2020)
  6. Holler, Martin; Weinmann, Andreas: Non-smooth variational regularization for processing manifold-valued data (2020)
  7. Osting, Braxton; Wang, Dong: Diffusion generated methods for denoising target-valued images (2020)
  8. Storath, Martin; Weinmann, Andreas: Wavelet sparse regularization for manifold-valued data (2020)
  9. Bergmann, R.; Laus, F.; Persch, J.; Steidl, G.: Recent advances in denoising of manifold-valued images (2019)
  10. Bergmann, Ronny; Tenbrinck, Daniel: A graph framework for manifold-valued data (2018)
  11. Bredies, K.; Holler, M.; Storath, M.; Weinmann, A.: Total generalized variation for manifold-valued data (2018)
  12. Celledoni, Elena; Eidnes, Sølve; Owren, Brynjulf; Ringholm, Torbjørn: Dissipative numerical schemes on Riemannian manifolds with applications to gradient flows (2018)
  13. Neumayer, Sebastian; Persch, Johannes; Steidl, Gabriele: Morphing of manifold-valued images inspired by discrete geodesics in image spaces (2018)
  14. Bergmann, Ronny; Fitschen, Jan Henrik; Persch, Johannes; Steidl, Gabriele: Iterative multiplicative filters for data labeling (2017)
  15. Bačák, Miroslav; Bergmann, Ronny; Steidl, Gabriele; Weinmann, Andreas: A second order nonsmooth variational model for restoring manifold-valued images (2016)
  16. Bergmann, Ronny; Chan, Raymond; Hielscher, Ralf; Persch, Johannes; Steidl, Gabriele: Restoration of manifold-valued images by half-quadratic minimization (2016)
  17. Bergmann, Ronny; Persch, Johannes; Steidl, Gabriele: A parallel Douglas-Rachford algorithm for minimizing ROF-like functionals on images with values in symmetric Hadamard manifolds (2016)
  18. Kim, Hyunwoo J.; Adluru, Nagesh; Bendlin, Barbara B.; Johnson, Sterling C.; Vemuri, Baba C.; Singh, Vikas: Canonical correlation analysis on SPD((n)) manifolds (2016)
  19. Weinmann, Andreas; Demaret, Laurent; Storath, Martin: Mumford-Shah and Potts regularization for manifold-valued data (2016)
  20. Wu, Xi; Yang, Zhipeng; Hu, Jinrong; Peng, Jing; He, Peiyu; Zhou, Jiliu: Diffusion-weighted images superresolution using high-order SVD (2016)