This is a collection of codes and demos developed by ICON Lab @ Bilkent University.
You are free to use, modify, and distribute any of the tools provided. However, please acknowledge this repository and cite the corresponding publications appropriately.
The following is a short description of the hosted toolboxes. Click each header to get directed to the corresponding repository.
Toolbox for data-driven parameter tuning strategy to automate hybrid PI-CS reconstructions. This technique is introduced in the following paper:
Ilicak E., Saritas E. U., Çukur T., "Automated Parameter Selection for Accelerated MRI Reconstruction via Low-Rank Modeling of Local k-Space Neighborhoods", Zeitschrift für Medizinische Physik, 2022. doi.org/10.1016/j.zemedi.2022.02.002
Toolbox for pGAN and cGAN deep networks. This technique is introduced in the following paper:
Dar S.U.H., Yurt M., Karacan L., Erdem A., Erdem E., Çukur T., "Image synthesis in multi-contrast MRI with conditional generative adversarial networks", IEEE Transactions on Medical Imaging, 2019. doi: 10.1109/TMI.2019.2901750
Toolbox for spatially informed voxelwise modeling. This technique is introduced in the following paper:
Çelik E., Dar S.U.H., Yılmaz Ö., Keleş Ü., Çukur T., (2019). "Spatially informed voxelwise modeling for naturalistic fMRI experiments. NeuroImage", 186, 741-757. doi: 10.1016/j.neuroimage.2018.11.044
Toolbox for self-tuning reconstruction of multi-coil multi-acquisition data using projection onto epigraph sets. This technique is introduced in the following paper:
Shahdloo M., Ilicak E., Tofighi M., Saritas E. U., Çetin A. E., and Çukur T., "Projection onto Epigraph Sets for Rapid Self-Tuning Compressed Sensing MRI", IEEE Transactions on Medical Imaging, 2018. doi: 10.1109/TMI.2018.2885599
Toolbox for reconstruction of multi-coil multi-acquisition data using calibration over tensors. This technique is introduced in the following paper:
Biyik E., Ilicak E., Cukur T. "Reconstruction by calibration over tensors for multi-coil multi-acquisition balanced SSFP imaging", Magnetic Resonance in Medicine, 2017. doi: 10.1002/mrm.26902.
Toolbox for generation of segregated sampling patterns for accelerated multi-acquisition MRI. This technique is introduced in the following paper:
Senel L. K., Kilic T., Gungor A., Kopanoglu E., Guven H. E., Saritas E. U., Koc A., Çukur T. "Statistically segregated k-space sampling for accelerating multiple-acquisition MRI". arXiv:1710.00532, 2017.
(c) ICON Lab 2022