Cleaning reconst scripts, part 3.

scilpy/io/mti.py

@@ -0,0 +1,163 @@
+# -*- coding: utf-8 -*-
+import logging
+import os
+import sys
+
+import nibabel as nib
+import numpy as np
+
+from scilpy.image.volume_math import concatenate
+from scilpy.io.image import load_img
+from scilpy.io.utils import get_acq_parameters
+from scilpy.reconst.mti import adjust_B1_map_intensities, smooth_B1_map, \
+    process_contrast_map
+
+
+def add_common_args_mti(p):
+    p.add_argument('--extended', action='store_true',
+                   help='If set, outputs the folder Complementary_maps.')
+    p.add_argument('--filtering', action='store_true',
+                   help='Gaussian filtering to remove Gibbs ringing. '
+                        'Not recommended.')
+
+    a = p.add_argument_group(
+        title='Acquisition parameters',
+        description='Acquisition parameters required for MTsat and ihMTsat '
+                    'calculation. \nThese are the excitation flip angles '
+                    '(a_PD, a_T1), in DEGREES, and \nrepetition times (TR_PD, '
+                    'TR_T1) of the PD and T1 images, in SECONDS. \nCan be '
+                    'given through json files (--in_jsons) or directly '
+                    '(--in_acq_parameters).')
+    a1 = a.add_mutually_exclusive_group(required='--in_mtoff_t1' in sys.argv)
+    a1.add_argument('--in_jsons', nargs=2,
+                    metavar=('PD_json', 'T1_json'),
+                    help='Path to MToff PD json file and MToff T1 json file, '
+                         'in that order. \nThe acquisition parameters will be '
+                         'extracted from these files. \nMust come from a '
+                         'Philips acquisition, otherwise, use '
+                         'in_acq_parameters.')
+    a1.add_argument('--in_acq_parameters', nargs=4, type=float,
+                    metavar=('PD flip angle', 'T1 flip angle',
+                             'PD repetition time', 'T1 repetition time'),
+                    help='Acquisition parameters in that order: flip angle of '
+                         'mtoff_PD, \nflip angle of mtoff_T1, repetition time '
+                         'of mtoff_PD, \nrepetition time of mtoff_T1')
+
+    b = p.add_argument_group(title='B1 correction')
+    b.add_argument('--in_B1_map',
+                   help='Path to B1 coregister map to MT contrasts.')
+    b.add_argument('--B1_correction_method',
+                   choices=['empiric', 'model_based'], default='empiric',
+                   help='Choice of B1 correction method. Choose between '
+                        'empiric and model-based. \nNote that the model-based '
+                        'method requires a B1 fitvalues file. \nBoth method '
+                        'will only correct the saturation measures. '
+                        '[%(default)s]')
+    b.add_argument('--B1_fitvalues', nargs='+',
+                   help='Path to B1 fitvalues files obtained externally. '
+                        'Should be one .mat \nfile per input MT-on image, '
+                        'given in this specific order: \npositive frequency '
+                        'saturation, negative frequency saturation.')
+    b.add_argument('--B1_nominal', default=100, type=float,
+                   help='Nominal value for the B1 map. For Philips, should be '
+                        '100. [%(default)s]')
+    b.add_argument('--B1_smooth_dims', default=5, type=int,
+                   help='Dimension of the squared window used for B1 '
+                        'smoothing, in number of voxels. [%(default)s]')
+
+
+def verifications_and_loading_mti(args, parser, input_maps_lists,
+                                  extended_dir, affine, contrast_names):
+    """
+    Common verifications for both MT and ihMT scripts.
+    """
+    # Verify that there is the same number of --positive, --negative,
+    # --in_mtoff_pd and --in_mtoff_t1
+    for curr_map_list in input_maps_lists[1:]:
+        if len(curr_map_list) != len(input_maps_lists[0]):
+            parser.error('Not the same number of echoes per contrast')
+
+    if len(input_maps_lists[0]) == 1:
+        single_echo = True
+    else:
+        single_echo = False
+
+    if args.in_B1_map and not args.in_mtoff_t1:
+        logging.warning('No B1 correction was applied because no MTsat or '
+                        'ihMTsat can be computed without the in_mtoff_t1.')
+
+    if args.B1_correction_method == 'model_based' and not args.B1_fitvalues:
+        parser.error('Fitvalues files must be given when choosing the '
+                     'model-based B1 correction method. Please use '
+                     '--B1_fitvalues.')
+
+    # Set TR and FlipAngle parameters. Required with --in_mtoff_t1, in which
+    # case one of --in_aqc_parameters or --in_jsons is set.
+    rep_times = None
+    flip_angles = None
+    if args.in_acq_parameters:
+        flip_angles = np.asarray(args.in_acq_parameters[:2]) * np.pi / 180.
+        rep_times = np.asarray(args.in_acq_parameters[2:]) * 1000
+        if rep_times[0] > 10000 or rep_times[1] > 10000:
+            logging.warning('Given repetition times do not seem to be given '
+                            'in seconds. MTsat results might be affected.')
+    elif args.in_jsons:
+        rep_times = []
+        flip_angles = []
+        for curr_json in args.in_jsons:
+            acq_parameter = get_acq_parameters(curr_json,
+                                               ['RepetitionTime', 'FlipAngle'])
+            if acq_parameter[0] > 10:
+                logging.warning('Repetition time found in {} does not seem to '
+                                'be given in seconds. MTsat and ihMTsat '
+                                'results might be affected.'.format(curr_json))
+            rep_times.append(acq_parameter[0] * 1000)  # convert ms.
+            flip_angles.append(acq_parameter[1] * np.pi / 180.)  # convert rad.
+
+    # Fix issue from the presence of invalide value and division by zero
+    np.seterr(divide='ignore', invalid='ignore')
+
+    # Load B1 image
+    B1_map = None
+    if args.in_B1_map and args.in_mtoff_t1:
+        B1_img = nib.load(args.in_B1_map)
+        B1_map = B1_img.get_fdata(dtype=np.float32)
+        B1_map = adjust_B1_map_intensities(B1_map, nominal=args.B1_nominal)
+        B1_map = smooth_B1_map(B1_map, wdims=args.B1_smooth_dims)
+        if args.B1_correction_method == 'model_based':
+            # Apply the B1 map to the flip angles for model-based correction
+            flip_angles[0] *= B1_map
+            flip_angles[1] *= B1_map
+        if args.extended:
+            nib.save(nib.Nifti1Image(B1_map, affine),
+                     os.path.join(extended_dir, "B1_map.nii.gz"))
+
+    # Define contrasts maps names
+    if args.filtering:
+        contrast_names = [curr_name + '_filter'
+                          for curr_name in contrast_names]
+    if single_echo:
+        contrast_names = [curr_name + '_single_echo'
+                          for curr_name in contrast_names]
+    if args.out_prefix:
+        contrast_names = [args.out_prefix + '_' + curr_name
+                          for curr_name in contrast_names]
+
+    # Compute contrasts maps
+    contrast_maps = []
+    for idx, curr_map in enumerate(input_maps_lists):
+        input_images = []
+        for image in curr_map:
+            img, _ = load_img(image)
+            input_images.append(img)
+        merged_curr_map = concatenate(input_images, input_images[0])
+        contrast_maps.append(process_contrast_map(merged_curr_map,
+                                                  filtering=args.filtering,
+                                                  single_echo=single_echo))
+        if args.extended:
+            nib.save(nib.Nifti1Image(contrast_maps[idx].astype(np.float32),
+                                     affine),
+                     os.path.join(extended_dir,
+                                  contrast_names[idx] + '.nii.gz'))
+
+    return single_echo, flip_angles, rep_times, B1_map, contrast_maps