Simulating 3D refractive index distributions of suspended cells

The introduction of holo-tomographic flow cytometry has unlocked the possibility of imaging the 3D refractive index (RI) distribution of suspended cells while they flow and rotate in microfluidic streams. Similarly, approaches that optically trap and rotate the samples can image them in suspension conditions. Great effort has been spent in developing robust algorithms for the tomogram estimation, as well as denoising and 3D segmentation algorithms. However, the lack of a ground-truth dataset for suspended cells significantly hinders the development of image processing pipelines, limiting the advancement of the associated technology field. Here we propose a novel method for simulating 3D refractive index tomograms of suspended cells. We start with prior knowledge of the statistics of the 3D RI distribution and morphometry of various cell sub-compartments gathered from holo-tomographic flow cytometry experiments and combined with literature data to create realistic 3D distributions. Next, we introduce a simple method to obtain a simulation of the tomogram obtainable from each cell, which approximates the effects of the limited numerical aperture of the system, the speckle noise and the inversion algorithm itself. As a benchmark for the simulator, we created a shared dataset of RI tomograms with various levels of complexity, simulating yeast eukaryotic cells at different budding stages with various phenotypes of cytoplasmic vacuoles, and the presence of cytoplasmic vacuoles and lipid droplets in monocyte cells. We believe that this shared dataset and the simulation method will contribute to the development of a wide plethora of tomogram estimation and processing algorithms.