Lenslet array tunable snapshot imaging spectrometer (LATIS) for hyperspectral fluorescence microscopy

Abstract

Snapshot hyperspectral imaging augments pixel dwell time and acquisition speeds over existing scanning systems, making it a powerful tool for fluorescence microscopy. While most snapshot systems contain fixed datacube parameters (x,y,λ), our novel snapshot system, called the lenslet array tunable snapshot imaging spectrometer (LATIS), demonstrates tuning its average spectral resolution from 22.66 nm (80x80x22) to 13.94 nm (88x88x46) over 485 to 660 nm. We also describe a fixed LATIS with a datacube of 200x200x27 for larger fieldof-view (FOV) imaging. We report <1 sec exposure times and high resolution fluorescence imaging with minimal artifacts. Tracking Using a High-Speed Hyperspectral Line-Scanning Microscope," PLoS One 8(5), e64320 (2013). 14. P. M. Kasili and T. Vo-Dinh, "Hyperspectral imaging system using acousto-optic tunable filter for flow cytometry applications," Cytometry A 69(8), 835-841 (2006).

Optimization of wavelength selection for multispectral image acquisition: a case study of atrial ablation lesions

“…Compared to scanning based systems, snapshot imagers provide longer dwell times per pixel. As such, these imagers are better suited for applications with dim and dynamic targets such as endocardial fluorescent imaging [13].…”

“…The system is capable of simultaneously acquiring 40 channels at a resolution of 350x350 pixels [17]. More recently, the same group reported using Lenslet array based tunable snapshot imaging spectrometry (LATIS) for high resolution fluorescence imaging with reported resolutions of 200x200 at 27 spectral channels and integration time of less than a second [13]. Other recently reported in-vivo systems include 4D snapshot hyperspectral video-endoscope [41], fiber-based prototype imaging spectrometer for oxygen saturation measurements [14] and Lyot filters based multispectral imagers [42].…”

“…Finding combinations of few spectral bands that are sufficient for lesion identification, would allow for simultaneous acquisition using the latest advances in fast scanning and high spatial resolution non-scanning imaging [13][14][15][16][17]. Overall, our studies offer several unbiased quantitative strategies as to how to limit the number of acquisition wavelengths while recognizing the target tissue with high accuracy.…”

Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array

“…Next to single-channel spectrometers, multiplexing of spectrally resolved speckle fields into hyperspectral imaging systems is of great interest. Compared to traditional approaches such as Integral Field Spectrometers [18,19], complex media can offer new opportunities for combining broadband transmission with high spectral resolution [20,21,22]. In the spatial domain, multimode fibers as well as multi-core fiber bundles are a topic of study for a variety of imaging applications such as remote sensing and endoscopy [23,24,25,26].…”

Snapshot fiber spectral imaging using speckle correlations and compressive sensing

“…A more desirable approach for many scenarios is the use of snapshot technologies, which acquire both spatial and spectral information in one measurement. Commonly seen in astronomy, Integral Field Spectrometers (IFSs) aim to acquire full hyperspectral data cubes within single snapshot images, with many based on lenslet arrays, fiber bundles, and slicing mirrors [1,2,3,4,5,6]. However, most devices rely on grating-based wavelength characterization, with device footprints scaling with spectral resolution.…”