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