296 citations · 526 across the 13 of their papers we have counts for
5 papers · 1 filter
A matrix-free Levenberg-Marquardt algorithm for efficient ptychographic phase retrieval
Saugat Kandel, S. Maddali, Youssef S G Nashed +3
The phase retrieval problem, where one aims to recover a complex-valued image from far-field intensity measurements, is a classic problem encountered in a range of imaging applicat…
Adorym: A multi-platform generic x-ray image reconstruction framework based on automatic differentiation
Ming Du, Saugat Kandel, Junjing Deng +7
We describe and demonstrate an optimization-based x-ray image reconstruction framework called Adorym. Our framework provides a generic forward model, allowing one code framework to…
Real-time 3D Nanoscale Coherent Imaging via Physics-aware Deep Learning
Henry Chan, Youssef S. G. Nashed, Saugat Kandel +4
Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging fr…
Three dimensions, two microscopes, one code: automatic differentiation for x-ray nanotomography beyond the depth of focus limit
Ming Du, Youssef S. G. Nashed, Saugat Kandel +2
Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering. Ad…
Using Automatic Differentiation as a General Framework for Ptychographic Reconstruction
Saugat Kandel, S. Maddali, Marc Allain +3
Coherent diffraction imaging methods enable imaging beyond lens-imposed resolution limits. In these methods, the object can be recovered by minimizing an error metric that quantifi…