def dwi_image(subject_id, timepoint, visit_str, visit_mri_list, mri_qc_subj):
"""
Args:
subject_id:
timepoint:
visit_str:
visit_mri_list:
mri_qc_subj:
Returns:
"""
from clinica.iotools.converters.adni_to_bids.adni_utils import replace_sequence_chars, select_image_qc
sel_image = select_image_qc(list(visit_mri_list.IMAGEUID), mri_qc_subj)
if sel_image is None:
return None
sel_scan = visit_mri_list[visit_mri_list.IMAGEUID == sel_image].iloc[0]
image_dict = {
'Subject_ID': subject_id,
'VISCODE': timepoint,
'Visit': visit_str,
'Sequence': replace_sequence_chars(sel_scan.SEQUENCE),
'Scan_Date': sel_scan['SCANDATE'],
'Study_ID': str(int(sel_scan.STUDYID)),
'Series_ID': str(int(sel_scan.SERIESID)),
'Image_ID': str(int(sel_scan.IMAGEUID)),
'Field_Strength': sel_scan.MAGSTRENGTH
}
return image_dict
def dwi_image(subject_id, timepoint, visit_str, visit_mri_list, mri_qc_subj):
"""
One image among those in the input list is chosen according to QC
and then correspoding metadata is extracted to a dictionary
Args:
subject_id: Subject identifier
timepoint: Visit code
visit_str: Visit name
visit_mri_list: List of images metadata
mri_qc_subj: Dataframe containing list of QC of scans for the subject
Returns: dictionary - contains image metadata
"""
from clinica.iotools.converters.adni_to_bids.adni_utils import replace_sequence_chars, select_image_qc
sel_image = select_image_qc(list(visit_mri_list.IMAGEUID), mri_qc_subj)
if sel_image is None:
return None
sel_scan = visit_mri_list[visit_mri_list.IMAGEUID == sel_image].iloc[0]
image_dict = {'Subject_ID': subject_id,
'VISCODE': timepoint,
'Visit': visit_str,
'Sequence': replace_sequence_chars(sel_scan.SEQUENCE),
'Scan_Date': sel_scan['SCANDATE'],
'Study_ID': str(int(sel_scan.STUDYID)),
'Series_ID': str(int(sel_scan.SERIESID)),
'Image_ID': str(int(sel_scan.IMAGEUID)),
'Field_Strength': sel_scan.MAGSTRENGTH}
return image_dict
def fmri_image(subject_id, timepoint, visit_str, visit_mri_list, mri_qc_subj):
"""
One image among those in the input list is chosen according to QC
and then correspoding metadata is extracted to a dictionary.
Args:
subject_id: Subject identifier
timepoint: Visit code
visit_str: Visit name
visit_mri_list: List of images metadata
mri_qc_subj: Dataframe containing list of QC of scans for the subject
Returns: dictionary - contains image metadata
"""
from clinica.iotools.converters.adni_to_bids.adni_utils import (
replace_sequence_chars,
select_image_qc,
)
mri_qc_subj.columns = [x.lower() for x in mri_qc_subj.columns]
sel_image = select_image_qc(list(visit_mri_list.IMAGEUID), mri_qc_subj)
if sel_image is None:
return None
sel_scan = visit_mri_list[visit_mri_list.IMAGEUID == sel_image].iloc[0]
image_dict = {
"Subject_ID": subject_id,
"VISCODE": timepoint,
"Visit": visit_str,
"Sequence": replace_sequence_chars(sel_scan.SEQUENCE),
"Scan_Date": sel_scan["SCANDATE"],
"Study_ID": str(int(sel_scan.STUDYID)),
"Series_ID": str(int(sel_scan.SERIESID)),
"Image_ID": str(int(sel_scan.IMAGEUID)),
"Field_Strength": sel_scan.MAGSTRENGTH,
}
return image_dict