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Gradient optical diffraction tomography
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DOI：10.1038/s42005-025-02416-3.png)
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Abstract
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Optical diffraction tomography (ODT) reconstructs the 3D refractive index (RI) distribution of transparent microsamples using angle-scanned holographic complex field measurements, enabling quantitative and label-free 3D imaging. High-quality ODT typically requires low-coherence illumination combined with a common-path, preferably shearing holographic setup to ensure stable interference. However, shearing configurations are limited to sparse samples due to their reliance on object-free regions for self-interference. Moreover, low coherence necessitates small shears, pushing many approaches towards gradient-based imaging that usually relies on error-prone phase integration and z-scanning, achieving only quasi-3D visualization. In this work we present Gradient Optical Diffraction Tomography (GODT) – a rigorous tomographic method that directly reconstructs the 3D RI derivative from the set of phase gradient measurements. GODT is validated with simulations and experiments on nano-printed cell phantom and fixed neural cells. It is shown that GODT can reveal fine sample structure with enhanced contrast and sensitivity to RI variations. Optical diffraction tomography (ODT) enables 3D imaging of transparent samples but is limited by coherence-related artifacts. We present Gradient ODT, which uses partially coherent light to achieve high signal-to-noise imaging and introduces refractive index gradients as a new, highly sensitive 3D contrast mechanism.
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