2.1.1.5. rpt_dosi.dosimetry

2.1.1.5.1. Classes

DoseComputation

DoseComputationWithPhantom

DoseComputationWithDoseRate

DoseMadsen2018

DoseHanscheid2017

DoseHanscheid2018

DoseMadsen2018DoseRate

DoseHanscheid2018DoseRate

DoseHanscheid2017DoseRate

2.1.1.5.2. Functions

dose_hanscheid2017(spect_bq_a, roi_a, ...)

Input img and ROI must be numpy arrays

dose_hanscheid2018(spect_bq_a, roi_a, ...)

Input image and ROI must be numpy arrays

dose_madsen2018_dose_rate(dose_rate_a, roi_a, ...)

dose_hanscheid2018_dose_rate(dose_rate_a, roi_a, ...)

dose_hanscheid2017_dose_rate(dose_rate_a, roi_a, ...)

dose_madsen2018(spect_Bq, roi, acq_time_h, svalue, ...)

Input image and ROI must be numpy arrays

fit_exp_linear(x, y)

decay_corrected_tac(t, a, decay_constant)

triexpo_fit(times, activities[, as_dict])

from https://github.com/jacksonmedphysics/TriExponential-Solver

triexpo_rmse(times, activities, decay_constant, A1, ...)

triexpo_param_from_dict(p)

triexpo_apply_from_dict(x, decay_constant_hours, p)

triexpo_apply(x, decay_constant_hours, A1, k1, A2, k2, ...)

test_compare_json_doses(json_ref, json_test[, tol])

get_dose_computation_class(name)

2.1.1.5.3. Module Contents

rpt_dosi.dosimetry.dose_hanscheid2017(spect_bq_a, roi_a, time_from_injection_h, volume_voxel_m_l, effective_time_h)[source]

Input img and ROI must be numpy arrays Input SPECT img must be in Bq

rpt_dosi.dosimetry.dose_hanscheid2018(spect_bq_a, roi_a, time_from_injection_h, s_value, mass_scaling)[source]

Input image and ROI must be numpy arrays - spect must be in Bq (not concentration) - acquisition time in hours - output is in Gray

rpt_dosi.dosimetry.dose_madsen2018_dose_rate(dose_rate_a, roi_a, time_from_injection_h, effective_time_h)[source]
rpt_dosi.dosimetry.dose_hanscheid2018_dose_rate(dose_rate_a, roi_a, time_from_injection_h)[source]
rpt_dosi.dosimetry.dose_hanscheid2017_dose_rate(dose_rate_a, roi_a, time_from_injection_h, roi_time_eff_h)[source]
rpt_dosi.dosimetry.dose_madsen2018(spect_Bq, roi, acq_time_h, svalue, mass_scaling, roi_time_eff_h)[source]

Input image and ROI must be numpy arrays - spect must be in Bq (not concentration) - svalue in mGy/MBq/s - time in hours - output is in Gray

rpt_dosi.dosimetry.fit_exp_linear(x, y)[source]
rpt_dosi.dosimetry.decay_corrected_tac(t, a, decay_constant)[source]
rpt_dosi.dosimetry.triexpo_fit(times, activities, as_dict=True)[source]

from https://github.com/jacksonmedphysics/TriExponential-Solver Pharmacokinetics backend of the VRAK Voxel dosimetry software reported in Med Phys. 2013 Nov;40(11):112503. doi: 10.1118/1.4824318. https://www.ncbi.nlm.nih.gov/pubmed/24320462

rpt_dosi.dosimetry.triexpo_rmse(times, activities, decay_constant, A1, k1, A2, k2, A3, k3)[source]
rpt_dosi.dosimetry.triexpo_param_from_dict(p)[source]
rpt_dosi.dosimetry.triexpo_apply_from_dict(x, decay_constant_hours, p)[source]
rpt_dosi.dosimetry.triexpo_apply(x, decay_constant_hours, A1, k1, A2, k2, A3, k3)[source]
rpt_dosi.dosimetry.test_compare_json_doses(json_ref, json_test, tol=0.001)[source]
class rpt_dosi.dosimetry.DoseComputation(ct: rpt_dosi.images.MetaImageCT, spect: rpt_dosi.images.MetaImageSPECT)[source]
name = None[source]
ct[source]
spect[source]
resample_like = 'ct'[source]
radionuclide = 'lu177'[source]
gaussian_sigma = None[source]
check_options()[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
init_resampling()[source]
init_results()[source]
class rpt_dosi.dosimetry.DoseComputationWithPhantom(method_name)[source]
phantom = None[source]
icrp_phantom_name = None[source]
icrp_radionuclide = None[source]
method_name[source]
get_phantom(radionuclide)[source]
class rpt_dosi.dosimetry.DoseComputationWithDoseRate(ct, dose_rate)[source]

Bases: DoseComputation

ct[source]
dose_rate[source]
scaling = 1.0[source]
init_resampling()[source]
class rpt_dosi.dosimetry.DoseMadsen2018(ct, spect)[source]

Bases: DoseComputation, DoseComputationWithPhantom

name = 'madsen2018'[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
class rpt_dosi.dosimetry.DoseHanscheid2017(ct, spect)[source]

Bases: DoseComputation

name = 'hanscheid2017'[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
class rpt_dosi.dosimetry.DoseHanscheid2018(ct, spect)[source]

Bases: DoseComputation, DoseComputationWithPhantom

name = 'hanscheid2018'[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
class rpt_dosi.dosimetry.DoseMadsen2018DoseRate(ct, dose_rate)[source]

Bases: DoseComputationWithDoseRate

name = 'madsen2018_dose_rate'[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
class rpt_dosi.dosimetry.DoseHanscheid2018DoseRate(ct, dose_rate)[source]

Bases: DoseComputationWithDoseRate

name = 'hanscheid2018_dose_rate'[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
class rpt_dosi.dosimetry.DoseHanscheid2017DoseRate(ct, dose_rate)[source]

Bases: DoseComputationWithDoseRate

name = 'hanscheid2017_dose_rate'[source]
run(rois: list[rpt_dosi.images.MetaImageROI])[source]
rpt_dosi.dosimetry.get_dose_computation_class(name)[source]