# Iterative Joint Ptychography-Tomography with Total Variation Regularization

## TL;DR

This paper introduces a novel iterative joint ptychography-tomography reconstruction method using ADMM and total variation regularization, enabling high-quality 3D imaging with fewer measurements and increased noise robustness.

## Contribution

It proposes a new joint reconstruction model and algorithm that outperform traditional two-step methods by allowing larger scan steps and improving image quality.

## Key findings

- Allows larger scan stepsizes in ptychography.
- Requires fewer measurements for accurate 3D reconstruction.
- Demonstrates increased robustness to noise.

## Abstract

In order to determine the 3D structure of a thick sample, researchers have recently combined ptychography (for high resolution) and tomography (for 3D imaging) in a single experiment. 2-step methods are usually adopted for reconstruction, where the ptychography and tomography problems are often solved independently. In this paper, we provide a novel model and ADMM-based algorithm to jointly solve the ptychography-tomography problem iteratively, also employing total variation regularization. The proposed method permits large scan stepsizes for the ptychography experiment, requiring less measurements and being more robust to noise with respect to other strategies, while achieving higher reconstruction quality results.