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DOE OSTI2016

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

PSTN-054: Updated estimates of the Rubin system throughput and expected LSST image depth

This document presents updated estimates, as of May 2022, of the Rubin system throughput and compares them to throughput requirements from the LSST Science Requirements Document. In addition, it uses these estimates to forecast LSST's median single-visit and co-added image depths for the current (OpSim v2.0) baseline LSST cadence simulation: (23.8, 24.5, 24.0, 23.4, 22.7, 22.0) and (25.6, 26.9, 26.9, 26.4, 25.6, 24.8) in ugrizy, respectively. In addition, it uses these estimates to forecast LSST’s median single-visit and co-added image depths for the current baseline LSST cadence simulation. Estimated system performance relies on actual measurements of the performance of various system hardware components, and on simulations where measurements are still unavailable. The updated performance estimates meet all the relevant requirements from the LSST Science Requirements Document. As our knowledge of the as-buit system continues to improve, updates to these estimates will continue to be provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Choroidal vasculature characteristics based choroid segmentation for enhanced depth imaging optical coherence tomography images

Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imaging optical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller’s layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, based on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors’ proposed method and manual segmentation drawn by experts were −11.43 μm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors’ method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Depth-resolved ballistic imaging in a low-depth-of-field optical Kerr gated imaging system

We demonstrate depth-resolved imaging in a ballistic imaging system, in which a heterodyned femtosecond optical Kerr gate is introduced to extract useful imaging photons for detecting an object hidden in turbid media and a compound lens is proposed to ensure both the depth-resolved imaging capability and the long working distance. Two objects of about 15-μm widths hidden in a polystyrene-sphere suspension have been successfully imaged with approximately 600-μm depth resolution. Modulation-transfer-function curves with the object in and away from the object plane have also been measured to confirm the depth-resolved imaging capability of the low-depth-of-field (low-DOF) ballistic imaging system. This imaging approach shows potential for application in research of the internal structure of highly scattering fuel spray.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Thermoacoustic imaging over large field of view for three-dimensional breast tumor localization: A phantom study

Purpose: Previous studies demonstrated that thermoacoustic imaging (TAI) has great potential for breast tumor detection. However, large field of view (FOV) imaging remains a long-standing challenge for three-dimensional (3D) breast tumor localization. Here, the authors propose a practical TAI system for noninvasive 3D localization of breast tumors with large FOV through the use of ultrashort microwave pulse (USMP). Methods: A USMP generator was employed for TAI. The energy density required for quality imaging and the corresponding microwave-to-acoustic conversion efficiency were compared with that of conventional TAI. The microwave energy distribution, imaging depth, resolution, and 3D imaging capabilities were then investigated. Finally, a breast phantom embedded with a laboratory-grown tumor was imaged to evaluate the FOV performance of the USMP TAI system, under a simulated clinical situation. Results: A radiation energy density equivalent to just 1.6%–2.2% of that for conventional submicrosecond microwave TAI was sufficient to obtain a thermoacoustic signal with the required signal-to-noise ratio. This result clearly demonstrated a significantly higher microwave-to-acoustic conversion efficiency of USMP TAI compared to that of conventional TAI. The USMP TAI system achieved 61 mm imaging depth and 12 × 12 cm{sup 2} microwave radiation area. The volumetric image of a copper target measured at depth of 4–6 cm matched well with the actual shape and the resolution reaches 230 μm. The TAI of the breast phantom was precisely localized to an accuracy of 0.1 cm over an 8 × 8 cm{sup 2} FOV. Conclusions: The experimental results demonstrated that the USMP TAI system offered significant potential for noninvasive clinical detection and 3D localization of deep breast tumors, with low microwave radiation dose and high spatial resolution over a sufficiently large FOV.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor

The importance of vegetation structure and biomass in controlling land-atmosphere exchange is widely recognized, but measurements of canopy structure are challenging, time consuming, and often rely on destructive methods. The Microsoft Kinect is an infrared sensor designed for video gaming that outputs synchronized color and depth images and that has the potential to allow rapid characterization of vegetation structure. We compared depth images from a Kinect sensor with manual measurements of plant structure and size for two species growing in a California grassland. The depth images agreed well with the horizontal and vertical measurements of plant size made manually. Similarly, the plant volumes calculated with a three-dimensional convex hulls approach was well related to plant biomass. The Kinect showed some limitations for ecological observation associated with a short measurement range and daytime light contamination. Nonetheless, the Kinect’s light weight, fast acquisition time, low power requirement, and cost make it a promising tool for rapid field surveys of canopy structure, especially in small-statured vegetation.

Microsoft Kinect↗
DOE OSTI2014

SU-E-I-11: Cascaded Linear System Model for Columnar CsI Flat Panel Imagers with Depth Dependent Gain and Blur

Purpose: To implement a depth dependent gain and blur cascaded linear system model (CLSM) for optimizing columnar structured CsI indirect conversion flat panel imager (FPI) for advanced imaging applications. Methods: For experimental validation, depth dependent escape efficiency, e(z), was extracted from PHS measurement of different CsI scintillators (thickness, substrate and light output). The inherent MTF and DQE of CsI was measured using high resolution CMOS sensor. For CLSM, e(z) and the depth dependent MTF(f,z), were estimated using Monte Carlo simulation (Geant4) of optical photon transport through columnar CsI. Previous work showed that Monte Carlo simulation for CsI was hindered by the non-ideality of its columnar structure. In the present work we allowed variation in columnar width with depth, and assumed diffusive reflective backing and columns. Monte Carlo simulation was performed using an optical point source placed at different depth of the CsI layer, from which MTF(z,f) and e(z) were computed. The resulting e(z) with excellent matching with experimental measurements were then applied to the CLSM, Monte Carlo simulation was repeated until the modeled MTF, DQE(f) also match experimental measurement. Results: For a 150 micron FOS HL type CsI, e(z) varies between 0.56 to 0.45, and the MTF at 14 cycles/mm varies between 62.1% to 3.9%, from the front to the back of the scintillator. The overall MTF and DQE(f) at all frequencies are in excellent agreement with experimental measurements at all frequencies. Conclusion: We have developed a CLSM for columnar CsI scintillators with depth dependent gain and MTF, which were estimated from Monte Carlo simulation with novel optical simulation settings. Preliminary results showed excellent agreement between simulation results and experimental measurements. Future work is aimed at extending this approach to optimize CsI screen optic design and sensor structure for achieving higher DQE(f) in cone-beam CT, which uses high kVp.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A data-driven approach to sampling matrix selection for compressive sensing

Sampling is a fundamental aspect of any implementation of compressive sensing. Typically, the choice of sampling method is guided by the reconstruction basis. However, this approach can be problematic with respect to certain hardware constraints and is not responsive to domain-specific context. We propose a method for defining an order for a sampling basis that is optimal with respect to capturing variance in data, thus allowing for meaningful sensing at any desired level of compression. We focus on the Walsh-Hadamard sampling basis for its relevance to hardware constraints, but our approach applies to any sampling basis of interest. We illustrate the effectiveness of our method on the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset, the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset, and a Colorado State University Swiss Ranger depth image dataset. The spectral datasets consist of simulant experiments, including releases of chemicals such as GAA and SF6. We combine our sampling and reconstruction with the adaptive coherence estimator (ACE) and bulk coherence for chemical detection and we incorporate an algorithmic threshold for ACE values to determine the presence or absence of a chemical. We compare results across sampling methods in this context. We have successful chemical detection at a compression rate of 90%. For all three datasets, we compare our sampling approach to standard orderings of sampling basis such as random, sequency, and an analog of sequency that we term `frequency.' In one instance, the peak signal to noise ratio was improved by over 30% across a test set of depth images.

compressive sensing, hyperspectral imaging, Walsh-↗
DOE OSTI2015

Phase-sensitive optical coherence tomography-based vibrometry using a highly phase-stable akinetic swept laser source

Phase-sensitive Optical Coherence Tomography (PhOCT) is an emerging tool for in vivo investigation of the vibratory function of the intact middle and inner ear. PhOCT is able to resolve micron scale tissue morphology in three dimensions as well as measure picometer scale motion at each spatial position. Most PhOCT systems to date have relied upon the phase stability offered by spectrometer detection. On the other hand swept laser source based PhOCT offers a number of advantages including balanced detection, long imaging depths, and high imaging speeds. Unfortunately the inherent phase instability of traditional swept laser sources has necessitated complex user developed hardware/software solutions to restore phase sensitivity. Here we present recent results using a prototype swept laser that overcomes these issues. The akinetic swept laser is electronically tuned and precisely controls sweeps without any mechanical movement, which results in high phase stability. We have developed an optical fiber based PhOCT system around the akinetic laser source that had a 1550 nm center wavelength and a sweep rate of 140 kHz. The stability of the system was measured to be 4.4 pm with a calibrated reflector, thus demonstrating near shot noise limited performance. Using this PhOCT system, we have acquired structural and vibratory measurements of the middle ear in a mouse model, post mortem. The quality of the results suggest that the akinetic laser source is a superior laser source for PhOCT with many advantages that greatly reduces the required complexity of the imaging system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Nanoscale Resolution 3D Snapshot Particle Tracking by Multifocal Microscopy

Accurate, precise, and rapid particle tracking in three dimensions remains a challenge; yet, its achievement will significantly enhance our understanding of living systems. We developed a multifocal microscopy (MFM) that allows snapshot acquisition of the imaging data, and an associated image processing approach, that together allow simultaneous 3D tracking of many fluorescent particles with nanoscale resolution. The 3D tracking was validated by measuring a known trajectory of a fluorescent bead with an axial accuracy of 19 nm through an image depth (axial range) of 3 pm and 4 nm precision of axial localization through an image depth of 4 pm. A second test obtained a uniform axial probability distribution and Brownian dynamics of beads diffusing in solution. We also validated the MFM approach by imaging fluorescent beads immobilized in gels and comparing the 3D localizations to their "ground truth" positions obtained from a confocal microscopy z-stack of finely spaced images. Finally, we applied our MFM and image processing approach to obtain 3D trajectories of insulin granules in pseudoislets of MIN6 cells to demonstrate its compatibility with complex biological systems. Our study demonstrates that multifocal microscopy allows rapid (video rate) and simultaneous 3D tracking of many "particles" with nanoscale accuracy and precision in a wide range of systems, including over spatial scales relevant to whole live cells.

3D Tracking↗
DOE OSTI2018

Tunable, Ultrafast Fiber-Laser between 1.15 μm and 1.35 μm for Harmonic Generation Microscopy in Human Skin

We demonstrate a fiber-optic ultrafast tunable source for harmonic generation microscopy (HGM) in human skin. The source is based on a 31-MHz Er-fiber laser followed by self-phase modulation enabled spectral selection (SESS). The resulting pulses are tunable between 1.15 and 1.35 μm with up to >10-nJ pulse energy and ~100-fs pulse duration. Here we employ this source to drive a scanning microscope for HGM imaging of ex vivo human skin. A systematic investigation on imaging depth versus excitation wavelength reveals that excitation wavelengths in the 1.15-1.25 μm range exhibit low optical attenuation within the tissue and allows larger imaging depth for HGM in human skin. HGM driven by fiber-based SESS sources constitutes an enabling tool for noninvasive virtual skin biopsy in clinical applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

System and method for controlling depth of imaging in tissues using fluorescence microscopy under ultraviolet excitation following staining with fluorescing agents

The present disclosure relates to a method for analyzing tissue specimens. In one implementation the method involves obtaining a tissue sample and exposing the sample to one or more fluorophores as contrast agents to enhance contrast of subcellular compartments of the tissue sample. The tissue sample is illuminated by an ultraviolet (UV) light having a wavelength between about 200 nm to about 400 nm, with the wavelength being selected to result in penetration to only a specified depth below a surface of the tissue sample. Inter-image operations between images acquired under different imaging parameters allow for improvement of the image quality via removal of unwanted image components. A microscope may be used to image the tissue sample and provide the image to an image acquisition system that makes use of a camera. The image acquisition system may create a corresponding image that is transmitted to a display system for processing and display.

36 MATERIALS SCIENCE↗
DOE OSTI2018

System and method for controlling depth of imaging in tissues using fluorescence microscopy under ultraviolet excitation following staining with fluorescing agents

A method is disclosed for analyzing a thin tissue sample and adapted to be supported on a slide. The tissue sample may be placed on a slide and exposed to one or more different exogenous fluorophores excitable in a range of about 300 nm-200 nm, and having a useful emission band from about 350 nm-900 nm, and including one or more fluorescent dyes or fluorescently labeled molecular probes that accumulate in tissue or cellular components. The fluorophores may be excited with a first wavelength of UV light between about 200 nm-290 nm. An optical system collects emissions from the fluorophores at a second wavelength, different from the first wavelength, which are generated in response to the first wavelength of UV light, to produce an image for analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

THE SLOAN DIGITAL SKY SURVEY STRIPE 82 IMAGING DATA: DEPTH-OPTIMIZED CO-ADDS OVER 300 deg{sup 2} IN FIVE FILTERS

We present and release co-added images of the Sloan Digital Sky Survey (SDSS) Stripe 82. Stripe 82 covers an area of ∼300 deg{sup 2} on the celestial equator, and has been repeatedly scanned 70-90 times in the ugriz bands by the SDSS imaging survey. By making use of all available data in the SDSS archive, our co-added images are optimized for depth. Input single-epoch frames were properly processed and weighted based on seeing, sky transparency, and background noise before co-addition. The resultant products are co-added science images and their associated weight images that record relative weights at individual pixels. The depths of the co-adds, measured as the 5σ detection limits of the aperture (3.''2 diameter) magnitudes for point sources, are roughly 23.9, 25.1, 24.6, 24.1, and 22.8 AB magnitudes in the five bands, respectively. They are 1.9-2.2 mag deeper than the best SDSS single-epoch data. The co-added images have good image quality, with an average point-spread function FWHM of ∼1'' in the r, i, and z bands. We also release object catalogs that were made with SExtractor. These co-added products have many potential uses for studies of galaxies, quasars, and Galactic structure. We further present and release near-IR J-band images that cover ∼90 deg{sup 2} of Stripe 82. These images were obtained using the NEWFIRM camera on the NOAO 4 m Mayall telescope, and have a depth of about 20.0-20.5 Vega magnitudes (also 5σ detection limits for point sources)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Quantum ghost imaging microscopy depth-of-field study

Quantum ghost imaging approaches have been proposed to enhance biological microscopy, for example, using 2D visible detectors to provide IR images or providing additional dimensions of spatial or spectral information. Toward the goal of making such imaging schemes practical, we compare image quality and depth-of-field between traditional images and ghost images at the same excitation levels. We measure how image quality and depth-of-field depend on the parameters of the entangled light produced using type-I spontaneous parametric down-conversion (SPDC). We use a pair of time-synchronized, photon-timing single-photon avalanche diode (SPAD) array detectors to capture two distinct microscope imaging paths simultaneously on a photon-pair-by-photon-pair basis: one in a traditional imaging pathway and the other a quantum ghost imaging pathway. We calculate the depth-of-field, resolution, contrast, and signal-to-noise ratio (SNR) through the parameter space of a β-Barium Borate (BBO) type-I bulk non-linear crystal length and angle. Our results provide a basis for choosing parameters for quantum ghost imaging with type-I SPDC sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

SU-F-J-206: Systematic Evaluation of the Minimum Detectable Shift Using a Range- Finding Camera

Purpose: The robotic table used for patient alignment in proton therapy is calibrated only at commissioning under well-defined conditions and table shifts may vary over time and with differing conditions. The purpose of this study is to systematically investigate minimum detectable shifts using a time-of-flight (TOF) range-finding camera for table position feedback. Methods: A TOF camera was used to acquire one hundred 424 × 512 range images from a flat surface before and after known shifts. Range was assigned by averaging central regions of the image across multiple images. Depth resolution was determined by evaluating the difference between the actual shift of the surface and the measured shift. Depth resolution was evaluated for number of images averaged, area of sensor over which depth was averaged, distance from camera to surface, central versus peripheral image regions, and angle of surface relative to camera. Results: For one to one thousand images with a shift of one millimeter the range in error was 0.852 ± 0.27 mm to 0.004 ± 0.01 mm (95% C.I.). For varying regions of the camera sensor the range in error was 0.02 ± 0.05 mm to 0.47 ± 0.04 mm. The following results are for 10 image averages. For areas ranging from one pixel to 9 × 9 pixels the range in error was 0.15 ± 0.09 to 0.29 ± 0.15 mm (1σ). For distances ranging from two to four meters the range in error was 0.15 ± 0.09 to 0.28 ± 0.15 mm. For an angle of incidence between thirty degrees and ninety degrees the average range in error was 0.11 ± 0.08 to 0.17 ± 0.09 mm. Conclusion: It is feasible to use a TOF camera for measuring shifts in flat surfaces under clinically relevant conditions with submillimeter precision.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗