swelling_tablet_fronts_d_k_from_mri_t2_or_img
Tool for calculating swelling tablet eroding front's diffusion rate D and the rate of the swelling k from time series of either T2-maps or MRI images in FDF or Text Image format. (Python 3)
https://github.com/beatawereszczynska/t1wir_to_t1wsr
Simulating T1-weighted saturation recovery MRI images for arbitrary values of TR from a set of T1-weighted inversion recovery MRI images. (Python 3)
mrisharingguide
We developed a guide for researchers in the Netherlands who want to share brain MRI data to help them get started.
https://github.com/beatawereszczynska/tiandte_wish
Calculating theoretical MRI images with both TI (T1-weighting) and TE (T2-weighting) of choice, from separate T1-weighted and T2-weighted sets of images. (Python 3)
https://github.com/beatawereszczynska/ti_te_wish
Simulating T1- and T2-weighted MRI images with arbitrary values of TI or TE, respectively. (Python 3)
breastdcedl
BreastDCEDL Pretreatment MRI scans of 2070 Breast cancer patients. A Deep Learning-Ready DCE-MRI Breast Cancer Dataset from I-SPY2 and I-SPY1 trials (1,2 and DUKE.
mri_k-space-derived_details_edges
k-space based details/edges detection in MRI images with optional k-space based denoising and detail control (on the example of Agilent FID data). (Python 3)
https://github.com/beatawereszczynska/k-space_masking_for_mri_denoising
Graduate k-space masking for MRI image denoising and blurring (on the example of Agilent FID data). (Python 3)
k-space_wght_msk_for_mri_denoising
k-space weighting and masking for denoising of MRI image without blurring or losing contrast, as well as for brightening of the objects in the image with simultaneous noise reduction (on the example of Agilent FID data). (Python 3)