--------------------------------------------------------------------------- REPLICA: An MRI image synthesis algorithm --------------------------------------------------------------------------- The files included implement the algorithm described in [1]. Given a set of training images of different contrasts (an atlas), train a random forest regressor to output values of a target contrast. Can use single resolution or multiresolution features (although the inputs to either pathway are different!). You can generate/see some (very sparse) documentation in the docs/ directory. ** Note that this package is not actively maintained and has been superseded by the synthit python package located here: https://github.com/jcreinhold/synthit ** This code has been tested on MATLAB 2017b and MATLAB 2018a. Code Author: Amod Jog (v1) Jacob Reinhold (v2) (jacob.reinhold@jhu.edu) --------------------------------------------------------------------------- References --------------------------------------------------------------------------- [1] A. Jog, et al., ``Random forest regression for magnetic resonance image synthesis'', Medical Image Analysis, 35:475-488, 2017. --------------------------------------------------------------------------- Project Structure --------------------------------------------------------------------------- replica | |---src (source code) | | | |---io (holds code to read in and output files) | | | nii (external module to handle NifTI files) | | | open_atlas (open nifti image and preprocess it) | | | open_lesionmask (open lesionmask and preprocess it) | | | save_synth (save/output synthesized image) | | | |---predict (functions for aligning speech parameters) | | | replica_predict (apply the trained random forest and synthesize images) | | | replica_predict_multires (same, but w/ multires features) | | | |---train (functions for automatically aligning and synthesizing speech) | | | replica_train (extract features and train the random forest for REPLICA) | | | replica_train_multires (same, but w/ multires features) | | | |---utilities (miscellaneous functions used in processing) | | | extract_context_patch (extract a context descriptor, see [1]) | | | wm_peak_normalize_T1w (scale T1w images by fixing the WM hist peak to 1000) | | | [not sure if this is actually for T1w, or just an old version] | | | wm_peak_normalize_T2w (scale T2w images by fixing the WM hist peak to 1000) | | | peakdet (detect local minima and maxima in a vector) | | | patch_indices (get indices that comprise a patch) | | | pad (pads the input image according to some specification) | | | wm_ref_normalize (routine [not used] for normalizing an image to a reference) | | | wm_peak_normalize_fcm (routine [not used] for normalizing wm peak w/ FCM) | | |---multires (routines specific to multiresolution pipeline) | | |---singleres (routines specific to single resolution pipeline) | |---tests (unit tests, demos) | | replica_demo (example single resolution REPLICA training and synthesis) | | replica_demo_multires (same, but multires) | |---docs (documentation)