An official website of the United States government
Imaging of surface-enhanced Raman scattering (SERS) nanoparticles (NPs) has been intensively studied for cancer detection due to its high sensitivity, unconstrained low signal-to-noise ratios, and multiplexing detection capability. Furthermore, conjugating SERS NPs with various biomarkers is straightforward, resulting in numerous successful studies on cancer detection and diagnosis. However, Raman spectroscopy only provides spectral data from an imaging area without co-registered anatomic context. This is not practical and suitable for clinical applications. Here, we propose a custom-made Raman spectrometer with computer-vision-based positional tracking and monocular depth estimation using deep learning (DL) for the visualization of 2D and 3D SERS NPs imaging, respectively. In addition, the SERS NPs used in this study (hyaluronic acid-conjugated SERS NPs) showed clear tumor targeting capabilities (target CD44 typically overexpressed in tumors) by anex vivoexperiment and immunohistochemistry. The combination of Raman spectroscopy, image processing, and SERS molecular imaging, therefore, offers a robust and feasible potential for clinical applications.
more »
« less
Full-field optical spectroscopy at a high spectral resolution using atomic vapors
Spectral imaging techniques extract spectral information using dispersive elements in combination with optical microscopes. For rapid acquisition, multiplexing spectral information along one dimension of imaged pixels has been demonstrated in hyperspectral imaging, as well as in Raman and Brillouin imaging. Full-field spectroscopy, i.e., multiplexing where imaged pixels are collected in 2D simultaneously while spectral analysis is performed sequentially, can increase spectral imaging speed, but so far has been attained at low spectral resolutions. Here, we extend 2D multiplexing to high spectral resolutions of ∼80 MHz (∼0.0001 nm) using high-throughput spectral discrimination based on atomic transitions.
more »
« less
- Award ID(s):
- 1942003
- PAR ID:
- 10392581
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Optics Express
- Volume:
- 31
- Issue:
- 3
- ISSN:
- 1094-4087; OPEXFF
- Format(s):
- Medium: X Size: Article No. 4334
- Size(s):
- Article No. 4334
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
High-power, short-pulse laser-driven fast electrons can rapidly heat and ionize a high-density target before it hydrodynamically expands. The transport of such electrons within a solid target has been studied using two-dimensional (2D) imaging of electron-induced Kα radiation. However, it is currently limited to no or picosecond scale temporal resolutions. Here, we demonstrate femtosecond time-resolved 2D imaging of fast electron transport in a solid copper foil using the SACLA x-ray free electron laser (XFEL). An unfocused collimated x-ray beam produced transmission images with sub-micron and ∼10 fs resolutions. The XFEL beam, tuned to its photon energy slightly above the Cu K-edge, enabled 2D imaging of transmission changes induced by electron isochoric heating. Time-resolved measurements obtained by varying the time delay between the x-ray probe and the optical laser show that the signature of the electron-heated region expands at ∼25% of the speed of light in a picosecond duration. Time-integrated Cu Kα images support the electron energy and propagation distance observed with the transmission imaging. The x-ray near-edge transmission imaging with a tunable XFEL beam could be broadly applicable for imaging isochorically heated targets by laser-driven relativistic electrons, energetic protons, or an intense x-ray beam.more » « less
-
null (Ed.)Holographic displays and computer-generated holography offer a unique opportunity in improving optical resolutions and depth characteristics of near-eye displays. The thermally-modulated Nanopho-tonic Phased Array (NPA), a new type of holographic display, affords several advantages, including integrated light source and higher refresh rates, over other holographic display technologies. However, the thermal phase modulation of the NPA makes it susceptible to the thermal proximity effect where heating one pixel affects the temperature of nearby pixels. Proximity effect correction (PEC) methods have been proposed for 2D Fourier holograms in the far field but not for Fresnel holograms at user-specified depths. Here we extend an existing PEC method for the NPA to Fresnel holograms with phase-only hologram optimization and validate it through computational simulations. Our method is not only effective in correcting the proximity effect for the Fresnel holograms of 2D images at desired depths but can also leverage the fast refresh rate of the NPA to display 3D scenes with time-division multiplexing.more » « less
-
Abstract Multidimensional photography can capture optical fields beyond the capability of conventional image sensors that measure only two-dimensional (2D) spatial distribution of light. By mapping a high-dimensional datacube of incident light onto a 2D image sensor, multidimensional photography resolves the scene along with other information dimensions, such as wavelength and time. However, the application of current multidimensional imagers is fundamentally restricted by their static optical architectures and measurement schemes—the mapping relation between the light datacube voxels and image sensor pixels is fixed. To overcome this limitation, we propose tunable multidimensional photography through active optical mapping. A high-resolution spatial light modulator, referred to as an active optical mapper, permutes and maps the light datacube voxels onto sensor pixels in an arbitrary and programmed manner. The resultant system can readily adapt the acquisition scheme to the scene, thereby maximising the measurement flexibility. Through active optical mapping, we demonstrate our approach in two niche implementations: hyperspectral imaging and ultrafast imaging.more » « less
-
null (Ed.)Abstract. Current cloud and aerosol identification methods for multispectral radiometers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS), employ multichannel spectral tests on individual pixels (i.e., fields of view). The use of the spatial information in cloud and aerosol algorithms has been primarily through statistical parameters such as nonuniformity tests of surrounding pixels with cloud classification provided by the multispectral microphysical retrievals such as phase and cloud top height. With these methodologies there is uncertainty in identifying optically thick aerosols, since aerosols and clouds have similar spectral properties in coarse-spectral-resolution measurements. Furthermore, identifying clouds regimes (e.g., stratiform, cumuliform) from just spectral measurements is difficult, since low-altitude cloud regimes have similar spectral properties. Recent advances in computer vision using deep neural networks provide a new opportunity to better leverage the coherent spatial information in multispectral imagery. Using a combination of machine learning techniques combined with a new methodology to create the necessary training data, we demonstrate improvements in the discrimination between cloud and severe aerosols and an expanded capability to classify cloud types. The labeled training dataset was created from an adapted NASA Worldview platform that provides an efficient user interface to assemble a human-labeled database of cloud and aerosol types. The convolutional neural network (CNN) labeling accuracy of aerosols and cloud types was quantified using independent Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and MODIS cloud and aerosol products. By harnessing CNNs with a unique labeled dataset, we demonstrate the improvement of the identification of aerosols and distinct cloud types from MODIS and VIIRS images compared to a per-pixel spectral and standard deviation thresholding method. The paper concludes with case studies that compare the CNN methodology results with the MODIS cloud and aerosol products.more » « less
