rpt_dosi.dosimetry
==================

.. py:module:: rpt_dosi.dosimetry


Classes
-------

.. autoapisummary::

   rpt_dosi.dosimetry.DoseComputation
   rpt_dosi.dosimetry.DoseComputationWithPhantom
   rpt_dosi.dosimetry.DoseComputationWithDoseRate
   rpt_dosi.dosimetry.DoseMadsen2018
   rpt_dosi.dosimetry.DoseHanscheid2017
   rpt_dosi.dosimetry.DoseHanscheid2018
   rpt_dosi.dosimetry.DoseMadsen2018DoseRate
   rpt_dosi.dosimetry.DoseHanscheid2018DoseRate
   rpt_dosi.dosimetry.DoseHanscheid2017DoseRate


Functions
---------

.. autoapisummary::

   rpt_dosi.dosimetry.dose_hanscheid2017
   rpt_dosi.dosimetry.dose_hanscheid2018
   rpt_dosi.dosimetry.dose_madsen2018_dose_rate
   rpt_dosi.dosimetry.dose_hanscheid2018_dose_rate
   rpt_dosi.dosimetry.dose_hanscheid2017_dose_rate
   rpt_dosi.dosimetry.dose_madsen2018
   rpt_dosi.dosimetry.fit_exp_linear
   rpt_dosi.dosimetry.decay_corrected_tac
   rpt_dosi.dosimetry.triexpo_fit
   rpt_dosi.dosimetry.triexpo_rmse
   rpt_dosi.dosimetry.triexpo_param_from_dict
   rpt_dosi.dosimetry.triexpo_apply_from_dict
   rpt_dosi.dosimetry.triexpo_apply
   rpt_dosi.dosimetry.test_compare_json_doses
   rpt_dosi.dosimetry.get_dose_computation_class


Module Contents
---------------

.. py:function:: dose_hanscheid2017(spect_bq_a, roi_a, time_from_injection_h, volume_voxel_m_l, effective_time_h)

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


.. py:function:: dose_hanscheid2018(spect_bq_a, roi_a, time_from_injection_h, s_value, mass_scaling)

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


.. py:function:: dose_madsen2018_dose_rate(dose_rate_a, roi_a, time_from_injection_h, effective_time_h)

.. py:function:: dose_hanscheid2018_dose_rate(dose_rate_a, roi_a, time_from_injection_h)

.. py:function:: dose_hanscheid2017_dose_rate(dose_rate_a, roi_a, time_from_injection_h, roi_time_eff_h)

.. py:function:: dose_madsen2018(spect_Bq, roi, acq_time_h, svalue, mass_scaling, roi_time_eff_h)

   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


.. py:function:: fit_exp_linear(x, y)

.. py:function:: decay_corrected_tac(t, a, decay_constant)

.. py:function:: triexpo_fit(times, activities, as_dict=True)

   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


.. py:function:: triexpo_rmse(times, activities, decay_constant, A1, k1, A2, k2, A3, k3)

.. py:function:: triexpo_param_from_dict(p)

.. py:function:: triexpo_apply_from_dict(x, decay_constant_hours, p)

.. py:function:: triexpo_apply(x, decay_constant_hours, A1, k1, A2, k2, A3, k3)

.. py:function:: test_compare_json_doses(json_ref, json_test, tol=0.001)

.. py:class:: DoseComputation(ct: rpt_dosi.images.MetaImageCT, spect: rpt_dosi.images.MetaImageSPECT)

   .. py:attribute:: name
      :value: None



   .. py:attribute:: ct


   .. py:attribute:: spect


   .. py:attribute:: resample_like
      :value: 'ct'



   .. py:attribute:: radionuclide
      :value: 'lu177'



   .. py:attribute:: gaussian_sigma
      :value: None



   .. py:method:: check_options()


   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


   .. py:method:: init_resampling()


   .. py:method:: init_results()


.. py:class:: DoseComputationWithPhantom(method_name)

   .. py:attribute:: phantom
      :value: None



   .. py:attribute:: icrp_phantom_name
      :value: None



   .. py:attribute:: icrp_radionuclide
      :value: None



   .. py:attribute:: method_name


   .. py:method:: get_phantom(radionuclide)


.. py:class:: DoseComputationWithDoseRate(ct, dose_rate)

   Bases: :py:obj:`DoseComputation`


   .. py:attribute:: ct


   .. py:attribute:: dose_rate


   .. py:attribute:: scaling
      :value: 1.0



   .. py:method:: init_resampling()


.. py:class:: DoseMadsen2018(ct, spect)

   Bases: :py:obj:`DoseComputation`, :py:obj:`DoseComputationWithPhantom`


   .. py:attribute:: name
      :value: 'madsen2018'



   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


.. py:class:: DoseHanscheid2017(ct, spect)

   Bases: :py:obj:`DoseComputation`


   .. py:attribute:: name
      :value: 'hanscheid2017'



   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


.. py:class:: DoseHanscheid2018(ct, spect)

   Bases: :py:obj:`DoseComputation`, :py:obj:`DoseComputationWithPhantom`


   .. py:attribute:: name
      :value: 'hanscheid2018'



   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


.. py:class:: DoseMadsen2018DoseRate(ct, dose_rate)

   Bases: :py:obj:`DoseComputationWithDoseRate`


   .. py:attribute:: name
      :value: 'madsen2018_dose_rate'



   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


.. py:class:: DoseHanscheid2018DoseRate(ct, dose_rate)

   Bases: :py:obj:`DoseComputationWithDoseRate`


   .. py:attribute:: name
      :value: 'hanscheid2018_dose_rate'



   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


.. py:class:: DoseHanscheid2017DoseRate(ct, dose_rate)

   Bases: :py:obj:`DoseComputationWithDoseRate`


   .. py:attribute:: name
      :value: 'hanscheid2017_dose_rate'



   .. py:method:: run(rois: list[rpt_dosi.images.MetaImageROI])


.. py:function:: get_dose_computation_class(name)