[CCPPETMR/Hackathon-SIRF] PET Operator (#2)
Matthias J. Ehrhardt
A SIRF Acquisition Model <=> A CIL Operator
A.direct(x)
A.adjoint(x)
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Edoardo Pasca
direct = forward
backward = adjoint
Matthias J. Ehrhardt
As discussed with @KrisThielemans we need to change direct slightly. It should contain only the linear part of the forward operator (important: needs to be documented!!!!).
Matthias J. Ehrhardt
We also want to have subset functionality in some way. It would be good to write in python A[i].direct(x)to project the ith subset.
Edoardo Pasca
Specifically this needs to create a AcquisitionModel and not call
acq_model = AcquisitionModelUsingRayTracingMatrix()
## avoid calling these to have only linear term
acq_model.set_additive_term(add)
acq_model.set_background_term(bck)
print('projecting image...')
# project the image to obtain simulated acquisition data
# data from raw_data_file is used as a template
acq_template = AcquisitionData(raw_data_file)
acq_model.set_up(acq_template, image)
simulated_data = acq_model.forward(image)
Matthias J. Ehrhardt
For the subsets, one could "hack" this into python as
class AcquisitionModelSubset():
def __init__(AcquisitionModelSubset(subset_num, num_subsets)):
self.AcquisitionModel = pet.AcquisitionModel(...)
self.subset_num = subset_num
self.num_subsets = num_subsets
def direct(self, x):
return self.AcquisitionModel.direct(subset_num=self.subset_num, num_subsets=self.num_subsets)
def adjoint(self x):
return self.AcquisitionModel.adjoint(subset_num=self.subset_num, num_subsets=self.num_subsets)
then with
A = [pet.AcquisitionModelSubset(subset_num=i, num_subsets=m) for i in range(m)]
one can iterate over all subsets as
for i in range(m):
A[i].direct(x)
This solution could be similarly adapted to the c code if people are interested.
Matthias J. Ehrhardt
I suppose this is done? @paskino