MISSING_TOOTH_NUMBER = [28, 29, 30]
ORIGINAL_NO_MISSING = []
#MISSING_TOOTH_NUMBER = []
NEIGHBOUR_TOOTH = [31]
NUMBER_SPLINE_GUIDED_POINTS = 100
# ---- Define global file paths
RESULT_TEM_BASE = "G:\\My Drive\\Project\\IntraOral Scanner Registration\\Point Cloud and Registration TEMP\\"
# ---- Extract features
source_stl_base = 'G:\My Drive\Project\IntraOral Scanner Registration\STL_pc\\'
target_dicom_base = 'G:\My Drive\Project\IntraOral Scanner Registration\Point Cloud and Registration Raw Data\DICOM_pc\\'
stl_file_name = 'new_stl_points_tooth'
dicom_file_name = 'new_dicom_points_tooth'
arch_ct_original = fe.FullArch(ORIGINAL_NO_MISSING, 'CT', 'CT')
arch_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS', 'IOS')
arch_ct = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'CT')
# convert ct features to IOS space with rigid transformation
arch_ct_to_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
# generate virtual landmarks using ct features with local ICP
arch_ct_in_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
# arch after curvilinear correction - original ios arch
arch_ios_curvilinear_correction = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS', 'IOS')
# arch after curvilinear correction - virtual ct features
arch_ct_in_ios_curvilinear_correction = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
for i in TOOTH_NUMBER:
print('reading tooth ', i)
new_dicom_path = target_dicom_base + dicom_file_name + np.str(i) + '.csv'
new_stl_path = source_stl_base + stl_file_name + np.str(i) + '.csv'
faro_measurement_base = "G:\\My Drive\\Project\\IntraOral Scanner Registration" \
"\\TRE_verification\\faro_measurement\\"
splint_base = "G:\\My Drive\\Project\\IntraOral Scanner Registration\\TRE_verification\\splint_geometry\\"
stl_file_name = 'new_stl_points_tooth'
dicom_file_name = 'new_dicom_points_tooth'
faro_file_name = 'faro_measurement'
splint_designed = 'designed_geometry.txt'
splint_ios = 'tested_geometry.txt'
# ---- Read splint measurement
splint_fiducial_ground = Yomiread.read_csv(splint_base + splint_designed, 4)[:, 1:]
splint_fiducial_ios = Yomiread.read_csv(splint_base + splint_ios, 4)[:, 1:]
# initialize arch classes
arch_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS', 'IOS')
arch_ct = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'CT')
# arch after 1st step correction (splint correction)
arch_ios_splint_correction = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS', 'IOS')
# convert ct features to IOS space with rigid transformation
arch_ct_to_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
#arch_ct_to_ios_fxt = fe.Fixture(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
# generate virtual landmarks using ct features with local ICP
arch_ct_in_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
#arch_ct_in_ios_fxt = fe.Fixture(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
# arch after curvilinear correction - original ios arch
arch_ios_curvilinear_correction = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS', 'IOS')
#MISSING_TOOTH_NUMBER_STEP2 = [17, 18, 19, 20, 21]
MISSING_TOOTH_NUMBER_STEP2 = [18, 19, 20]
NEIGHBOUR_TOOTH_STEP2 = [17, 21]
# ---- Define global file paths
RESULT_TEM_BASE = "G:\\My Drive\\Project\\IntraOral Scanner Registration\\Point Cloud and Registration TEMP\\"
# ---- Extract features
source_stl_base = 'G:\My Drive\Project\IntraOral Scanner Registration\STL_pc\\'
target_dicom_base = 'G:\My Drive\Project\IntraOral Scanner Registration\Point Cloud and Registration Raw Data\DICOM_pc\\'
stl_file_name = 'new_stl_points_tooth'
dicom_file_name = 'new_dicom_points_tooth'
arch_ct_original = fe.Fixture(MISSING_TOOTH_NUMBER, 'CT', 'CT')
arch_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS', 'IOS')
arch_ct = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'CT')
# convert ct features to IOS space with rigid transformation
arch_ct_to_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
arch_ct_to_ios_fxt = fe.Fixture(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
# generate virtual landmarks using ct features with local ICP
arch_ct_in_ios = fe.FullArch(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
arch_ct_in_ios_fxt = fe.Fixture(MISSING_TOOTH_NUMBER, 'CT', 'IOS')
# arch after curvilinear correction - original ios arch
arch_ios_curvilinear_correction = fe.FullArch(MISSING_TOOTH_NUMBER, 'IOS',
'IOS')
arch_ios_fxt_curvilinear_correction = fe.Fixture(MISSING_TOOTH_NUMBER,
'IOS', 'IOS')
# arch after curvilinear correction - virtual ct features
arch_ct_in_ios_curvilinear_correction = fe.FullArch(