def single_sino(sino: np.ndarray,
cor: ScalarCoR,
proj_angles: ProjectionAngles,
recon_params: ReconstructionParameters,
progress: Optional[Progress] = None) -> np.ndarray:
assert sino.ndim == 2, "Sinogram must be a 2D image"
sino = BaseRecon.prepare_sinogram(sino, recon_params)
image_width = sino.shape[1]
if astra_mutex.locked():
LOG.warning("Astra recon already in progress. Waiting")
with astra_mutex:
vectors = vec_geom_init2d(proj_angles, 1.0,
cor.to_vec(image_width).value)
vol_geom = astra.create_vol_geom((image_width, image_width))
proj_geom = astra.create_proj_geom('parallel_vec', image_width,
vectors)
cfg = astra.astra_dict(recon_params.algorithm)
cfg['FilterType'] = recon_params.filter_name
with _managed_recon(sino, cfg, proj_geom,
vol_geom) as (alg_id, rec_id):
astra.algorithm.run(alg_id, iterations=recon_params.num_iter)
return astra.data2d.get(rec_id)
def single_sino(sino: np.ndarray, cor: ScalarCoR,
proj_angles: ProjectionAngles,
recon_params: ReconstructionParameters) -> np.ndarray:
assert sino.ndim == 2, "Sinogram must be a 2D image"
sino = BaseRecon.sino_recon_prep(sino)
image_width = sino.shape[1]
vectors = vec_geom_init2d(proj_angles, 1.0,
cor.to_vec(image_width).value)
vol_geom = astra.create_vol_geom((image_width, image_width))
proj_geom = astra.create_proj_geom('parallel_vec', image_width,
vectors)
cfg = astra.astra_dict(recon_params.algorithm)
cfg['FilterType'] = recon_params.filter_name
with _managed_recon(sino, cfg, proj_geom,
vol_geom) as (alg_id, rec_id):
astra.algorithm.run(alg_id, iterations=recon_params.num_iter)
return astra.data2d.get(rec_id)
def single_sino(sino: np.ndarray, cor: ScalarCoR,
proj_angles: ProjectionAngles,
recon_params: ReconstructionParameters) -> np.ndarray:
assert sino.ndim == 2, "Sinogram must be a 2D image"
assert sino.shape[0] == len(
proj_angles.value), f"Number of projection angles {len(proj_angles.value)} does not equal" \
f" the number of projections {sino.shape[0]}. This can happen if loading subset of" \
f" projections, and using projection angles from a log file."
image_width = sino.shape[1]
vectors = vec_geom_init2d(proj_angles, 1.0,
cor.to_vec(image_width).value)
vol_geom = astra.create_vol_geom((image_width, image_width))
proj_geom = astra.create_proj_geom('parallel_vec', image_width,
vectors)
cfg = astra.astra_dict(recon_params.algorithm)
cfg['FilterType'] = recon_params.filter_name
with _managed_recon(sino, cfg, proj_geom,
vol_geom) as (alg_id, rec_id):
astra.algorithm.run(alg_id, iterations=recon_params.num_iter)
return astra.data2d.get(rec_id)