Inverse Scattering Problem

The inverse scattering problem aims to reconstruct the properties of an object from measurements of scattered waves, a crucial task in various fields like medical imaging and non-destructive testing. Current research heavily utilizes deep learning, incorporating neural networks into iterative methods like Born iterations or employing diffusion models and implicit representations to improve reconstruction accuracy and efficiency. These advancements address challenges posed by the ill-posed nature of the problem, particularly in handling limited data, noise, and high frequencies, leading to more robust and computationally feasible solutions for diverse applications.