# Regularized Inverse Holographic Volume Reconstruction for 3D Particle Tracking

## TL;DR

This paper introduces a regularized inverse holographic reconstruction method that enhances 3D particle tracking by improving resolution, handling higher concentrations, and reducing computational costs through GPU acceleration.

## Contribution

The paper presents a novel inverse problem approach with fused lasso regularization for full volumetric particle reconstruction, enabling better accuracy and efficiency in DIH.

## Key findings

- Accurate 3D particle reconstruction demonstrated on synthetic and experimental data.
- Significant reduction in computational cost using GPU processing.
- Extended DIH capabilities to high concentration microorganism and microfiber applications.

## Abstract

The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution and utilizing GPU processing, we dramatically reduce the computational cost usually associated with inverse reconstruction approaches. We demonstrate the accuracy of the proposed method using synthetic and experimental holograms. Finally, we present two practical applications (high concentration microorganism swimming and microfiber rotation) to extend the capabilities of DIH beyond what was possible using prior methods.