Code

• MR_CSS

  Generalized Parameter Estimation and Optimal Experimental Design in Multi-Echo Gradient-Echo-Based Chemical Species Separation

  from the article Diefenbach, M. N., Liu, C., & Karampinos, D. C., Generalized parameter estimation in multi-echo gradient-echo-based chemical species separation, Quantitative Imaging in Medicine and Surgery, 10(3), 554–567 (2020). http://dx.doi.org/10.21037/qims.2020.02.07

  also

  Diefenbach, M. N., Liu, C., & Karampinos, D. C., Extending the signal models of the ismrm fat–water toolbox: generalized parameter estimation in multi-echo gradient-echo-based chemical species separation, (pp. 18) (2019). Singapore

  and

  Diefenbach, M. N., Ruschke, S., & Karampinos, D. C., A generalized formulation for parameter estimation in mr signals of multiple chemical species, In , Proceedings 25. Annual Meeting International Society for Magnetic Resonance in Medicine (pp. 5181) (2017). Honolulu, Hawaii: http://archive.ismrm.org/2017/5181.html.

• qsm_esp

  matlab and python code to compute 1D metrics to assess QSM reconstructions

  Diefenbach, M. N., Böhm, C., Meineke, J., Liu, C., & Karampinos, D. C., One-Dimensional k-Space Metrics on Cone Surfaces for Quantitative Susceptibility Mapping, Proceedings 27. Annual Meeting International Society for Magnetic Resonance in Medicine (pp. 0322) (2019). Montreal, Canada: https://cds.ismrm.org/protected/19MPresentations/abstracts/0322.html.

• MRI_field_contributions

  Example MATLAB code to perform the estimation and demodulation of field map contributions in magnetic resonance water–fat imaging from the article

  Diefenbach, M. N., Ruschke, S., Eggers, H., Meineke, J., Rummeny, E. J., & Karampinos, D. C., Improving chemical shift encoding-based water-fat separation based on a detailed consideration of magnetic field contributions, Magnetic Resonance in Medicine, 80(3), 990–1004 (2018). http://dx.doi.org/10.1002/mrm.27097

• trabecular_bone_QSM

  Example source code (MATLAB) to perform Quantitative Susceptibility Mapping (QSM) to measure trabecular bone density from the article

  Diefenbach, M. N., Meineke, J., Ruschke, S., Baum, T., Gersing, A., Karampinos, D. C., On the Sensitivity of Quantitative Susceptibility Mapping for Measuring Trabecular Bone Density,

  also contains the implementation of the VARPRO solver for chemical species separation (CSS) described in

  Diefenbach, M. N., Ruschke, S., & Karampinos, D. C., A generalized formulation for parameter estimation in mr signals of multiple chemical species, Proceedings 25. Annual Meeting International Society for Magnetic Resonance in Medicine (pp. 5181) (2017). Honolulu, Hawaii. http://archive.ismrm.org/2017/5181.html

• vatsatseg

  vatsatseg is a python implementation of the matlab segmentation tool “SAT_VAT_segmentation” to segment Visceral and Subcutaneous Adipose Tissue (VAT, SAT) in water-fat MRI images used in

  Shen, J., Baum, T., Cordes, C., Ott, B., Skurk, T., Kooijman, H., Rummeny, E. J., …, Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat mri: application to weight-loss in obesity, European Journal of Radiology, 85(9), 1613–1621 (2016). http://dx.doi.org/10.1016/j.ejrad.2016.06.006

• citeISMRM

  Commandline tool to extract bibtex entries for ISMRM abstracts from http://archive.ismrm.org

• mrseqdia

  LaTeX package to create pulse sequence diagrams in magnetic resonance imaging