Noise-robust one-bit diffraction tomography and optimal dose fractionation

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, 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?