Deep-learning-assisted Fourier transform imaging spectroscopy for hyperspectral fluorescence imaging.

Hyperspectral fluorescence imaging is widely used when multiple fluorescent probes with close emission peaks are required. In particular, Fourier transform imaging spectroscopy (FTIS) provides unrivaled spectral resolution; however, the imaging throughput is very low due to the amount of interferogram sampling required. In this work, we apply deep learning to FTIS and show that the interferogram sampling can be drastically reduced by an order of magnitude without noticeable degradation in the image quality. For the demonstration, we use bovine pulmonary artery endothelial cells stained with three fluorescent dyes and 10 types of fluorescent beads with close emission peaks. Further, we show that the deep learning approach is more robust to the translation stage error and environmental vibrations. Thereby, the He-Ne correction, which is typically required for FTIS, can be bypassed, thus reducing the cost, size, and complexity of the FTIS system. Finally, we construct neural network models using Hyperband, an automatic hyperparameter selection algorithm, and compare the performance with our manually-optimized model.

Hyperspectral three-dimensional absorption imaging using snapshot optical tomography.

Hyperspectral imaging (HSI) records a series of two-dimensional (2D) images for different wavelengths to provide the chemical fingerprint at each pixel. Combining HSI with a tomographic data acquisition method, we can obtain the chemical fingerprint of a sample at each point in three-dimensional (3D) space. The so-called 3D HSI typically suffers from low imaging throughput due to the requirement of scanning the wavelength and rotating the beam or sample. In this paper we present an optical system which captures the entire four-dimensional (4D), i.e., 3D structure and 1D spectrum, dataset of a sample with the same throughput of conventional HSI systems. Our system works by combining snapshot projection optical tomography (SPOT) which collects multiple projection images with a single snapshot, and Fourier-transform spectroscopy (FTS) which results in superior spectral resolution by collecting and processing a series of interferogram images. Using this hyperspectral SPOT system we imaged the volumetric absorbance of dyed polystyrene microbeads, oxygenated red blood cells (RBCs), and deoxygenated RBCs. The 4D optical system demonstrated in this paper provides a tool for high-throughput chemical imaging of complex microscopic specimens.

Hyperspectral Three-Dimensional Fluorescence Imaging Using Snapshot Optical Tomography.

Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection optical tomography (SPOT) and Fourier-transform spectroscopy (FTS). SPOT allows us to instantaneously acquire the projection images corresponding to different viewing angles, while FTS allows us to perform hyperspectral imaging at high spectral resolution. Using fluorescent beads and sunflower pollens, we demonstrate the imaging performance of the developed system.