sairyscan.reconstruction.IFEDDenoising#
- class sairyscan.reconstruction.IFEDDenoising(inner_ring_index: int = 7, epsilon: str | float = 0.3, reg_inner: float = 0.995, reg_outer: float = 0.995, weighting: float = 0.9, join_denoising: bool = False)#
Reconstruct a high resolution image with a ISFED method including a denoising step
The denoising is performed on the two terms of the ISFED image difference using the SPITFIR(e) algorithm.
- Parameters:
inner_ring_index – Index of the last detector of the inner ring [7, 19],
epsilon – weighting parameter for the ISFED difference second term. If epsilon=’map’, epsilon is an automatic estimated weight map using the SURE criterion. If epsilon=’mode’, epsilon is a float which corresponds to the main mode of the SURE map. Otherwise, epsilon can be fixed to any float value,
reg_inner – Regularization for denoising of the first term of ISFED reconstruction,
reg_outer – Regularization for the denoising of the second term of the SFED reconstruction,
weighting – Weighting parameter of the SPITFIR(e) denoising model. Must be in [0, 1], with value close to 0 for sparse signal and close to one otherwise.
- __init__(inner_ring_index: int = 7, epsilon: str | float = 0.3, reg_inner: float = 0.995, reg_outer: float = 0.995, weighting: float = 0.9, join_denoising: bool = False)#
Methods
__init__([inner_ring_index, epsilon, ...])add_observer(observer)Add an observer
notify(message)Notify progress to observers
progress(value)Notify progress to observers