Noise-Robust One-Bit Diffraction Tomography and Optimal Dose Fractionation

TL;DR

This paper introduces a noise-robust 1-bit diffraction tomography method using coded apertures, employing advanced algorithms and theory to optimize 3D imaging quality under high noise and dose constraints.

Contribution

It proposes a novel noise-robust reconstruction framework for 1-bit diffraction tomography and reveals optimal dose fractionation strategies independent of total dose.

Findings

Optimal dose fractionation at SNR near 1

Effective recovery under high noise conditions

Use of random matrix theory in reconstruction

Abstract

This study presents a noise-robust framework for 1-bit diffraction tomography, a novel imaging approach that relies on intensity-only binary measurements obtained through coded apertures. The proposed reconstruction scheme leverages random matrix theory and iterative algorithms to effectively recover 3D object structures under high-noise conditions. A key contribution is the numerical investigation of dose fractionation, revealing optimal performance at a signal-to-noise ratio near 1, {\em independent of the total dose}. This finding addresses the question: How to distribute a given level of total radiation energy among different tomographic views in order to optimize the quality of reconstruction?