Bastien Rigaud, PhD Laboratoire Traitement du Signal et de l'Image (LTSI), INSERM U1099 Campus de Beaulieu, Université de Rennes 1 35042 Rennes, FRANCE [email protected]
def compute_multi_organs():
# define model
deformable_model = BuildModel(dataloader=ImageReaderWriter)
input_features = {
'fixed_bladder_path': r'C:\Data\Data_test\Vessie_ext_0.nii.gz',
'moving_bladder_path': r'C:\Data\Data_test\Vessie_ext_1.nii.gz',
'fixed_prostate_path': r'C:\Data\Data_test\Prostate_0.nii.gz',
'moving_prostate_path': r'C:\Data\Data_test\Prostate_1.nii.gz',
'fixed_rectum_path': r'C:\Data\Data_test\Rectum_ext_0.nii.gz',
'moving_rectum_path': r'C:\Data\Data_test\Rectum_ext_1.nii.gz',
}
deformable_model.set_processors([
GetSITKInfo(input_keys=('fixed_bladder', 'fixed_prostate', 'fixed_rectum',
'moving_bladder', 'moving_prostate', 'moving_rectum')),
SimplifyMask(input_keys=('fixed_bladder', 'fixed_prostate', 'fixed_rectum',
'moving_bladder', 'moving_prostate', 'moving_rectum'),
output_keys=('fixed_bladder', 'fixed_prostate', 'fixed_rectum',
'moving_bladder', 'moving_prostate', 'moving_rectum'),
type_keys=('opening', 'opening', 'opening', 'opening', 'opening', 'opening',),
radius_keys=(2, 2, 2, 2, 2, 2,)),
ConvertMaskToPoly(input_keys=('fixed_bladder', 'fixed_prostate', 'fixed_rectum',
'moving_bladder', 'moving_prostate', 'moving_rectum'),
output_keys=('fpoly_bladder', 'fpoly_prostate', 'fpoly_rectum',
'mpoly_bladder', 'mpoly_prostate', 'mpoly_rectum')),
SITKToNumpy(input_keys=('fixed_bladder', 'fixed_prostate', 'fixed_rectum',
'moving_bladder', 'moving_prostate', 'moving_rectum'),
output_keys=('fixed_bladder', 'fixed_prostate', 'fixed_rectum',
'moving_bladder', 'moving_prostate', 'moving_rectum')),
ACVDResampling(input_keys=('fpoly_bladder', 'fpoly_prostate', 'fpoly_rectum',
'mpoly_bladder', 'mpoly_prostate', 'mpoly_rectum'),
output_keys=('fpoly_bladder', 'fpoly_prostate', 'fpoly_rectum',
'mpoly_bladder', 'mpoly_prostate', 'mpoly_rectum'),
nb_points=(750, 500, 750, 750, 500, 750,)),
JoinPoly(input_key_list=['fpoly_bladder', 'fpoly_prostate', 'fpoly_rectum'], output_key='xpoly',
use_scalar=True),
JoinPoly(input_key_list=['mpoly_bladder', 'mpoly_prostate', 'mpoly_rectum'], output_key='ypoly',
use_scalar=True),
CreateDVF(reference_keys=('xpoly', 'ypoly',), deformed_keys=('ft_poly', 'bt_poly',),
output_keys=('ft_dvf', 'bt_dvf',), run_post_process=True),
DistanceBasedMetrics(reference_keys=('xpoly', 'ypoly',), pre_process_keys=('ypoly', 'xpoly',),
post_process_keys=('bt_poly', 'ft_poly',), paired=False),
GetZNormParameters(input_keys=('xpoly', 'ypoly'), centroid_keys=('xpoly_centroid', 'ypoly_centroid'),
scale_keys=('xpoly_scale', 'ypoly_scale')),
ZNormPoly(input_keys=('xpoly', 'ypoly',),
output_keys=('xpoly', 'ypoly',),
post_process_keys=('xpoly', 'ypoly',),
centroid_keys=('xpoly_centroid', 'ypoly_centroid',),
scale_keys=('xpoly_scale', 'ypoly_scale',)),
ZNormPoly(input_keys=(), output_keys=('ft_poly', 'bt_poly'), post_process_keys=('ft_poly', 'bt_poly'),
centroid_keys=('ypoly_centroid', 'xpoly_centroid'), scale_keys=('ypoly_scale', 'xpoly_scale')),
CopyKey(input_keys=('xpoly_centroid', 'ypoly_centroid', 'xpoly_scale', 'ypoly_scale'),
output_keys=('bt_poly_centroid', 'ft_poly_centroid', 'bt_poly_scale', 'ft_poly_scale'))
])
deformable_model.set_cost_functions(
STPSRPM(xpoly_key='xpoly', ypoly_key='ypoly', use_scalar_vtk=False, passband=[0.01, 0.1, 1])
)
# build model
deformable_model.load_data(input_features)
deformable_model.pre_process(input_features)
deformable_model.run_cost_function(input_features)
deformable_model.post_process(input_features)
plot_vtk(input_features['ft_dvf'], input_features['ypoly'])def compute_tubular():
# define model
deformable_model = BuildModel(dataloader=ImageReaderWriter)
input_features = {
'fixed_rectum_path': r'C:\Data\Data_test\Rectum_ext_0.nii.gz',
'moving_rectum_path': r'C:\Data\Data_test\Rectum_ext_1.nii.gz',
}
deformable_model.set_processors([
GetSITKInfo(input_keys=('fixed_rectum', 'moving_rectum')),
SimplifyMask(input_keys=('fixed_rectum', 'moving_rectum'),
output_keys=('fixed_rectum', 'moving_rectum'),
type_keys=('opening', 'opening',),
radius_keys=(2, 2,)),
ConvertMaskToPoly(input_keys=('fixed_rectum', 'moving_rectum'),
output_keys=('fpoly_rectum', 'mpoly_rectum')),
SITKToNumpy(input_keys=('fixed_rectum', 'moving_rectum'),
output_keys=('fixed_rectum', 'moving_rectum')),
ACVDResampling(input_keys=('fpoly_rectum', 'mpoly_rectum'),
output_keys=('xpoly', 'ypoly'),
nb_points=(1000, 1000,)),
ExtractCenterline(input_keys=('fixed_rectum', 'moving_rectum',),
output_keys=('fixed_centerline', 'moving_centerline',)),
ComputeLaplacianCorrespondence(input_keys=('fixed_rectum', 'moving_rectum',),
centerline_keys=('fixed_centerline', 'moving_centerline',),
output_keys=('fixed_correspondence', 'moving_correspondence',),
spacing_keys=('fixed_rectum_spacing', 'moving_rectum_spacing',),
dilate_centerline=False),
CenterlineToPolydata(input_keys=('fixed_centerline', 'moving_centerline',),
output_keys=('fpoly_centerline', 'mpoly_centerline',),
origin_keys=('fixed_rectum_origin', 'moving_rectum_origin'),
spacing_keys=('fixed_rectum_spacing', 'moving_rectum_spacing')),
CenterlineProjection(input_keys=('xpoly', 'ypoly',),
centerline_keys=('fpoly_centerline', 'mpoly_centerline',),
correspondence_keys=('fixed_correspondence', 'moving_correspondence',),
output_keys=('xpoly', 'ypoly',),
origin_keys=('fixed_rectum_origin', 'moving_rectum_origin',),
spacing_keys=('fixed_rectum_spacing', 'moving_rectum_spacing',)),
CreateDVF(reference_keys=('fpoly_centerline',), deformed_keys=('mpoly_centerline',),
output_keys=('centerline_dvf',), run_pre_process=True),
CreateDVF(reference_keys=('xpoly', 'ypoly',), deformed_keys=('ft_poly', 'bt_poly',),
output_keys=('ft_dvf', 'bt_dvf',), run_post_process=True),
DistanceBasedMetrics(reference_keys=('xpoly', 'ypoly'), pre_process_keys=('ypoly', 'xpoly'),
post_process_keys=('bt_poly', 'ft_poly'), paired=False),
GetZNormParameters(input_keys=('xpoly', 'ypoly'), centroid_keys=('xpoly_centroid', 'ypoly_centroid'),
scale_keys=('xpoly_scale', 'ypoly_scale')),
ZNormPoly(input_keys=('xpoly', 'ypoly', 'fpoly_centerline', 'mpoly_centerline'),
output_keys=('xpoly', 'ypoly', 'fpoly_centerline', 'mpoly_centerline'),
post_process_keys=('xpoly', 'ypoly', 'fpoly_centerline', 'mpoly_centerline'),
centroid_keys=('xpoly_centroid', 'ypoly_centroid', 'xpoly_centroid', 'ypoly_centroid'),
scale_keys=('xpoly_scale', 'ypoly_scale', 'xpoly_scale', 'ypoly_scale')),
ZNormPoly(input_keys=(), output_keys=('ft_poly', 'bt_poly'), post_process_keys=('ft_poly', 'bt_poly'),
centroid_keys=('ypoly_centroid', 'xpoly_centroid'),
scale_keys=('ypoly_scale', 'xpoly_scale')),
CopyKey(input_keys=('xpoly_centroid', 'ypoly_centroid', 'xpoly_scale', 'ypoly_scale'),
output_keys=('bt_poly_centroid', 'ft_poly_centroid', 'bt_poly_scale', 'ft_poly_scale'))
])
deformable_model.set_cost_functions(
STPSRPM(xpoly_key='xpoly', ypoly_key='ypoly', xlm_key='fpoly_centerline', ylm_key='mpoly_centerline',
use_scalar_vtk=True, scalars_name='Length', passband=[0.01, 0.1, 1])
)
# build model
deformable_model.load_data(input_features)
deformable_model.pre_process(input_features)
deformable_model.run_cost_function(input_features)
deformable_model.post_process(input_features)
plot_vtk(input_features['ft_dvf'], input_features['ypoly'])Run:
pip install -r requirements.txt
List of required libraries:
This framework needs ArrayFire DLL/sources and Arrayfire-python (cpu, OpenCL, or CUDA backend) https://arrayfire.com/
- Rigaud, B., Cazoulat, G., Vedam, S., Venkatesan, A. M., Peterson, C. B., Taku, N., ... & Brock, K. K. (2020). Modeling complex deformations of the sigmoid colon between external beam radiation therapy and brachytherapy images of cervical cancer. International Journal of Radiation Oncology* Biology* Physics, 106(5), 1084-1094.
- Rigaud, B., Simon, A., Gobeli, M., Leseur, J., Duvergé, L., Williaume, D., ... & De Crevoisier, R. (2018). Statistical shape model to generate a planning library for cervical adaptive radiotherapy. IEEE transactions on medical imaging, 38(2), 406-416.