added Siemens_mMR_NEMA_IQ_lowcounts

SIRF_data_preparation/Siemens_mMR_NEMA_IQ_lowcounts/prepare_mMR_NEMA_IQ_data.py

@@ -0,0 +1,48 @@
+import argparse
+import logging
+import os
+
+from ..data_utilities import prepare_challenge_Siemens_data, the_data_path, the_orgdata_path
+
+this_directory = os.path.dirname(__file__)
+repo_directory = os.path.dirname(this_directory)
+challenge_data_path = os.path.join(repo_directory, 'data')
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description='SyneRBI PETRIC Siemens mMR NEMA IQ data preparation script.')
+
+    parser.add_argument('--log', type=str, default='warning')
+    parser.add_argument('--start', type=float, default=0)
+    parser.add_argument('--end', type=float, default=100)
+    parser.add_argument('--raw_data_path', type=str, default=None)
+    args = parser.parse_args()
+
+    if args.log in ['debug', 'info', 'warning', 'error', 'critical']:
+        level = eval(f'logging.{args.log.upper()}')
+        logging.basicConfig(level=level)
+        logging.info(f"Setting logging level to {args.log.upper()}")
+
+    start = args.start
+    end = args.end
+
+    if args.raw_data_path is None:
+        data_path = the_orgdata_path('Siemens_mMR_NEMA_IQ', 'raw', 'NEMA_IQ')
+    else:
+        data_path = args.raw_data_path
+
+    data_path = os.path.abspath(data_path)
+    logging.debug(f"Raw data path: {data_path}")
+
+    intermediate_data_path = the_orgdata_path('Siemens_mMR_NEMA_IQ_lowcounts', 'processing')
+    challenge_data_path = the_data_path('Siemens_mMR_NEMA_IQ_lowcounts')
+
+    os.makedirs(challenge_data_path, exist_ok=True)
+    os.chdir(challenge_data_path)
+    os.makedirs(intermediate_data_path, exist_ok=True)
+
+    f_template = os.path.join(data_path, 'mMR_template_span11.hs')
+
+    prepare_challenge_Siemens_data(data_path, challenge_data_path, intermediate_data_path, '20170809_NEMA_',
+                                   '60min_UCL.l.hdr', 'MUMAP_UCL.v', 'MUMAP_UCL.hv', 'UCL.n', 'norm.n.hdr', f_template,
+                                   'prompts', 'mult_factors', 'additive_term', 'randoms', 'attenuation_factor',
+                                   'attenuation_correction_factor', 'scatter', start, end)

SIRF_data_preparation/dataset_settings.py

@@ -4,8 +4,8 @@
 from petric import DATA_SLICES
 
 DATA_SUBSETS = {
-    'Siemens_mMR_NEMA_IQ': 7, 'Siemens_mMR_ACR': 7, 'NeuroLF_Hoffman_Dataset': 16, 'Mediso_NEMA_IQ': 12,
-    'Siemens_Vision600_thorax': 5}
+    'Siemens_mMR_NEMA_IQ': 7, 'Siemens_mMR_NEMA_IQ_lowcounts': 7, 'Siemens_mMR_ACR': 7, 'NeuroLF_Hoffman_Dataset': 16,
+    'Mediso_NEMA_IQ': 12, 'Siemens_Vision600_thorax': 5}
 
 
 @dataclass

petric.py

@@ -248,6 +248,7 @@ def get_image(fname):
 
 DATA_SLICES = {
     'Siemens_mMR_NEMA_IQ': {'transverse_slice': 72, 'coronal_slice': 109},                 # 'sagittal_slice': 89
+    'Siemens_mMR_NEMA_IQ_lowcounts': {'transverse_slice': 72, 'coronal_slice': 109, 'sagittal_slice': 89},
     'Siemens_mMR_ACR': {'transverse_slice': 99},
     'NeuroLF_Hoffman_Dataset': {'transverse_slice': 72},
     'Mediso_NEMA_IQ': {'transverse_slice': 22, 'coronal_slice': 89, 'sagittal_slice': 66},