Fluorescence Diffraction Tomography using Explicit Neural Fields

TL;DR

This paper introduces fluorescence diffraction tomography with explicit neural fields to reconstruct 3D refractive index of phase objects from reflection mode fluorescence images, enabling high-resolution, in vivo compatible multimodal imaging.

Contribution

It develops a novel FDT method using explicit neural fields, differential multi-slice rendering, and partially coherent masks for accurate 3D RI reconstruction from fluorescence data.

Findings

Successfully reconstructed 3D RI of bovine myotubes in vitro

Achieved high-resolution, high-accuracy 3D imaging of biological samples

Demonstrated effective reflection-mode fluorescence tomography

Abstract

Simultaneous imaging of fluorescence-labeled and label-free phase objects in the same sample provides distinct and complementary information. Most multimodal fluorescence-phase imaging operates in transmission mode, capturing fluorescence images and phase images separately or sequentially, which limits their practical application in vivo. Here, we develop fluorescence diffraction tomography (FDT) with explicit neural fields to reconstruct the 3D refractive index (RI) of phase objects from diffracted fluorescence images captured in reflection mode. The successful reconstruction of 3D RI using FDT relies on four key components: a coarse-to-fine structure, self-calibration, a differential multi-slice rendering model, and partially coherent masks. The explicit representation integrates with the coarse-to-fine structure for high-speed, high-resolution reconstruction, while the differential multi-slice rendering model enables self-calibration of fluorescence illumination, ensuring accurate forward image prediction and RI reconstruction. Partially coherent masks efficiently resolve discrepancies between the coherent light model and partially coherent light data. FDT successfully reconstructs the RI of 3D cultured label-free bovine myotubes in a 530 $\times$ 530 $\times$ 300 $\mu m^3$ volume at 1024 $\times$ 1024 pixels across 24 $z$-layers from fluorescence images, demonstrating high resolution and high accuracy 3D RI reconstruction of bulky and heterogeneous biological samples in vitro.