Ptychographic Reconstruction
Cross-source consensus on Ptychographic Reconstruction from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Risks & contraindications
Comparisons
Highlighted claims
- Ptychographic reconstruction speed is a practical bottleneck because modern beamlines acquire data faster than iterative algorithms can reconstruct it. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction
- Classical ptychographic methods recover phase by enforcing diffraction-intensity and overlap constraints repeatedly. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction
- Reconstruction uses a forward model in which the probe and object patch produce an exit wave that is Fourier transformed to predict diffraction intensity. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction
- Classical methods can handle experimental imperfections but require substantial computation. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction