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lots_im_parameters.py
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lots_im_parameters.py
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## General output full path (note to user: you can change this variable)
## This variable will be overriden if input files are .mat
output_filedir = "/mnt/storage/MRI_dataset/LOTS_IM_results_mini"
output_filedir = "/mnt/Storage/ADNI_20x3_2015/LOTS_IM_results_mini"
## Set setting of LOTS-IM's calculation
## Default: True (default) --> 3D LOTS-IM (volume based calculation)
## Otherwise (False): 2D LOTS-IM (slice based calculation)
set_3d = True
## Size of source and target patches.
## Must be in the form of python's list data structure.
## Default: patch_size = [1,2,4,8]
patch_size = [1,2,4,8]
## Weights for age map blending produced by different size of source/target patches
## Must be in the form of python's list data structure.
## Its length must be the same as 'patch_size' variable.
## Default: blending_weights = [0.65,0.2,0.1,0.05]
blending_weights = [0.65,0.2,0.1,0.05]
## Used only for automatic calculation for all number of samples
## NOTE: Smaller number of samples makes computation faster (please refer to the manuscript).
## Samples used for IAM calculation
## Default: num_samples_all = [512]
num_samples_all = [64,128]
## Uncomment line below and comment line above if you want to run all different number of samples
# num_samples_all = [64, 128, 256, 512, 1024, 2048]
## Weight of distance function to blend maximum difference and average difference between source
## and target patches. Default: alpha=0.5. Input value should be between 0 and 1 (i.e. floating).
alpha = 0.5
## Thresholds the target patches to prevent including patches containing hyper-intensities.
## Default : threshold_patches = None.
# thrsh_patches = 0.05
thrsh_patches = None
## Save JPEG outputs
## Default: save_jpeg = True
save_jpeg = True
## Delete all intermediary files/folders, saving some spaces in the hard disk drive.
## Default: delete_intermediary = True
delete_intermediary = True