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DOE OSTI2015

WE-EF-210-08: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in Ultrasound Images Using Patch-Based Anatomical Feature

Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage. During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a useful tool for image-guided interventions in prostate-cancer diagnosis and treatment. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-IeP3-07: High-Resolution, High-Sensitivity Imaging and Quantification of Intratumoral Distributions of Gold Nanoparticles Using a Benchtop L-Shell XRF Imaging System

Purpose: To demonstrate the ability to perform high-resolution imaging and quantification of sparse distributions of gold nanoparticles (GNPs) within ex vivo tumor samples using a highly-sensitive benchtop L-shell x-ray fluorescence (XRF) imaging system. Methods: An optimized L-shell XRF imaging system was assembled using a tungsten-target x-ray source (operated at 62 kVp and 45 mA). The x-rays were filtered (copper: 0.08 mm & aluminum: 0.04 mm) and collimated (lead: 5 cm thickness, 3 cm aperture diameter) into a cone-beam in order to irradiate small samples or objects. A collimated (stainless steel: 4 cm thickness, 2 mm aperture diameter) silicon drift detector, capable of 2D translation, was placed at 90° with respect to the beam to acquire XRF/scatter spectra from regions of interest. Spectral processing involved extracting XRF signal from background, followed by attenuation correction using a Compton scatter-based normalization algorithm. Calibration phantoms with water/GNPs (0 and 0.00001–10 mg/cm{sup 3}) were used to determine the detection limit of the system at a 10-second acquisition time. The system was then used to map the distribution of GNPs within a 12×11×2 mm{sup 3} slice excised from the center of a GNP-loaded ex vivo murine tumor sample; a total of 110 voxels (2.65×10{sup −3} cm{sup 3}) were imaged with 1.3-mm spatial resolution. Results: The detection limit of the current cone-beam benchtop L-shell XRF system was 0.003 mg/cm{sup 3} (3 ppm). Intratumoral GNP concentrations ranging from 0.003 mg/cm{sup 3} (3 ppm) to a maximum of 0.055 mg/cm{sup 3} (55 ppm) and average of 0.0093 mg/cm{sup 3} (9.3 ppm) were imaged successfully within the ex vivo tumor slice. Conclusion: The developed cone-beam benchtop L-shell XRF imaging system can immediately be used for imaging of ex vivo tumor samples containing low concentrations of GNPs. With minor finetuning/optimization, the system can be directly adapted for performing routine preclinical in vivo imaging tasks. Supported by NIH/NCI grant R01CA155446 This investigation was supported by NIH/NCI grant R01CA155446.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Considerations for three-dimensional image reconstruction from experimental data in coherent diffractive imaging

The Datasets folder contains 3 datasets, corresponding to the datasets mentioned in the article with 670, 2691 and 586 images. The Runs folder has all the runs used. Besides the images itself it also contains tags for each image under `/entry_1/image_1/detector_and_photon_corrected/tags`. The `headings` attribute gives the name of each tag. The `Jonas Strict` tag corresponds to the 670 images, the `Redflamingo` tag to the 2691 images and the `Redflamingo_Ida_subset` tag to the 586 images. The final dataset with 260 images can be obtained from `Datasets/amoc6914-Redflamingo-manual-586.h5` and use the `/model/diameterNM` group to select the 260 images with size closest to 214 nm.

AMO↗

DOE OSTI2016

IMAGING AN 80 au RADIUS DUST RING AROUND THE F5V STAR HD 157587

We present H -band near-infrared polarimetric imaging observations of the F5V star HD 157587 obtained with the Gemini Planet Imager (GPI) that reveal the debris disk as a bright ring structure at a separation of ∼80–100 au. The new GPI data complement recent Hubble Space Telescope /STIS observations that show the disk extending out to over 500 au. The GPI image displays a strong asymmetry along the projected minor axis as well as a fainter asymmetry along the projected major axis. We associate the minor and major axis asymmetries with polarized forward scattering and a possible stellocentric offset, respectively. To constrain the disk geometry, we fit two separate disk models to the polarized image, each using a different scattering phase function. Both models favor a disk inclination of ∼70° and a 1.5 ± 0.6 au stellar offset in the plane of the sky along the projected major axis of the disk. We find that the stellar offset in the disk plane, perpendicular to the projected major axis is degenerate with the form of the scattering phase function and remains poorly constrained. The disk is not recovered in total intensity due in part to strong adaptive optics residuals, but we recover three point sources. Considering the system’s proximity to the galactic plane and the point sources’ positions relative to the disk, we consider it likely that they are background objects and unrelated to the disk’s offset from the star.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

THE GINI COEFFICIENT AS A MORPHOLOGICAL MEASUREMENT OF STRONGLY LENSED GALAXIES IN THE IMAGE PLANE

Characterization of the morphology of strongly lensed galaxies is challenging because images of such galaxies are typically highly distorted. Lens modeling and source plane reconstruction is one approach that can provide reasonably undistorted images from which morphological measurements can be made, though at the expense of a highly spatially variable telescope point-spread function (PSF) when mapped back to the source plane. Unfortunately, modeling the lensing mass is a time- and resource-intensive process, and in many cases there are too few constraints to precisely model the lensing mass. If, however, useful morphological measurements could be made in the image plane rather than the source plane, it would bypass this issue and obviate the need for a source reconstruction process for some applications. We examine the use of the Gini coefficient as one such measurement. Because it depends on the cumulative distribution of the light of a galaxy, but not the relative spatial positions, the fact that surface brightness is conserved by lensing means that the Gini coefficient may be well preserved by strong gravitational lensing. Through simulations, we test the extent to which the Gini coefficient is conserved, including by effects due to PSF convolution and pixelization, to determine whether it is invariant enough under lensing to be used as a measurement of galaxy morphology that can be made in the image plane.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

MO-DE-207-04: Imaging educational program on solutions to common pediatric imaging challenges

This imaging educational program will focus on solutions to common pediatric imaging challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. The educational program will begin with a detailed discussion of the optimal configuration of fluoroscopes for general pediatric procedures. Following this introduction will be a focused discussion on the utility of Dual Energy CT for imaging children. The third lecture will address the substantial challenge of obtaining consistent image post -processing in pediatric digital radiography. The fourth and final lecture will address best practices in pediatric MRI including a discussion of ancillary methods to reduce sedation and anesthesia rates. Learning Objectives: To learn techniques for optimizing radiation dose and image quality in pediatric fluoroscopy To become familiar with the unique challenges and applications of Dual Energy CT in pediatric imaging To learn solutions for consistent post-processing quality in pediatric digital radiography To understand the key components of an effective MRI safety and quality program for the pediatric practice.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Porosity detection in electron beam-melted Ti-6Al-4V using high-resolution neutron imaging and grating-based interferometry

A high-resolution neutron tomography system and a grating-based interferometer are used to explore electron beam-melted titanium test objects. The high-resolution neutron tomography system (attenuation-based imaging) has a pixel size of 6.4 µm, appropriate for detecting voids near 25 µm over a (1.5 cm) 3 volume. The neutron interferometer provides dark-field (small-angle scattering) images with a pixel size of 30 µm. Moreover, the interferometer can be tuned to a scattering length, in this case, 1.97 µm, with a field-of-view of (6 cm)3. The combination of high-resolution imaging with grating-based interferometry provides a way for nondestructive testing of defective titanium samples. A chimney-like pore structure was discovered in the attenuation and dark-field images along one face of an electron beam-melted (EBM) Ti-6Al-4V cube. Tomographic reconstructions of the titanium samples are utilized as a source for a binary volume and for skeletonization of the pores. As a result, the dark-field volume shows features with dimensions near and smaller than the interferometer auto-correlation scattering length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Impact of Computed Tomography Image Quality on Image-Guided Radiation Therapy Based on Soft Tissue Registration

Purpose: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. Methods and Materials: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan. Results: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively. Conclusions: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Plasmonic nanorod probes’ journey inside plant cells for in vivo SERS sensing and multimodal imaging

Nanoparticle-based platforms are gaining strong interest in plant biology and bioenergy research to monitor and control biological processes in whole plants. However, in vivo monitoring of biomolecules using nanoparticles inside plant cells remains challenging due to the impenetrability of the plant cell wall to nanoparticles beyond the exclusion limits (5-20 nm). To overcome this physical barrier, we have designed unique bimetallic silver-coated gold nanorods (AuNR@Ag) capable of entering plant cells, while conserving key plasmonic properties in the near-infrared (NIR). To demonstrate cellular internalization and tracking of the nanorods inside plant tissue, we used a comprehensive multimodal imaging approach that included transmission electron microscopy (TEM), confocal fluorescence microscopy, two-photon luminescence (TPL), X-ray fluorescence microscopy (XRF), and photoacoustics imaging (PAI). We successfully acquired SERS signals of nanorods in vivo inside plant cells of tobacco leaves. On the same leaf samples, we applied orthogonal imaging methods, TPL and PAI techniques for in vivo imaging of the nanorods. This study first demonstrates the intracellular internalization of AuNR@Ag inside whole plant systems for in vivo SERS analysis in tobacco cells. This work demonstrates the potential of this nanoplatform as a new nanotool for intracellular in vivo biosensing for plant biology.

Cupil-Garcia, Vanessa↗

DOE OSTI2014

Soft x-ray backlighting of cryogenic implosions using a narrowband crystal imaging system (invited)

A high-performance cryogenic DT inertial confinement fusion implosion experiment is an especially challenging backlighting configuration because of the high self-emission of the core at stagnation and the low opacity of the DT shell. High-energy petawatt lasers such as OMEGA EP promise significantly improved backlighting capabilities by generating high x-ray intensities and short emission times. A narrowband x-ray imager with an astigmatism-corrected bent quartz crystal for the Si He{sub α} line at ∼1.86 keV was developed to record backlit images of cryogenic direct-drive implosions. A time-gated recording system minimized the self-emission of the imploding target. A fast target-insertion system capable of moving the backlighter target ∼7 cm in ∼100 ms was developed to avoid interference with the cryogenic shroud system. With backlighter laser energies of ∼1.25 kJ at a 10-ps pulse duration, the radiographic images show a high signal-to-background ratio of >100:1 and a spatial resolution of the order of 10 μm. The backlit images can be used to assess the symmetry of the implosions close to stagnation and the mix of ablator material into the dense shell.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

FAR-ULTRAVIOLET SPECTRAL IMAGES OF THE VELA SUPERNOVA REMNANT: SUPPLEMENTS AND COMPARISONS WITH OTHER WAVELENGTH IMAGES

We present the improved far-ultraviolet (FUV) emission-line images of the entire Vela supernova remnant (SNR) using newly processed Spectroscopy of Plasma Evolution from Astrophysical Radiation/Far-Ultraviolet Imaging Spectrograph (SPEAR/FIMS) data. The incomplete C III {lambda}977 and O VI {lambda}{lambda}1032, 1038 images presented in the previous study are updated to cover the whole region. The C IV {lambda}{lambda}1548, 1551 image with a higher resolution and new images at Si IV {lambda}{lambda}1394, 1403, O IV] {lambda}1404, He II {lambda}1640.5, and O III] {lambda}{lambda}1661, 1666 are also shown. Comparison of emission-line ratios for two enhanced FUV regions reveals that the FUV emissions of the east-enhanced FUV region may be affected by nonradiative shocks of another very young SNR, the Vela Jr. SNR (RX J0852.0-4622, G266.6-1.2). This result is the first FUV detection that is likely associated with the Vela Jr. SNR, supporting previous arguments that the Vela Jr. SNR is close to us. The comparison of the improved FUV images with soft X-ray images shows that an FUV filamentary feature forms the boundary of the northeast-southwest asymmetrical sections of the X-ray shell. The southwest FUV features are characterized as the region where the Vela SNR is interacting with slightly denser ambient medium within the dim X-ray southwest section. From a comparison with the H{alpha} image, we identify a ring-like H{alpha} feature overlapped with an extended hot X-ray feature of similar size and two local peaks of C IV emission. Their morphologies are expected when the H{alpha} ring is in direct contact with the near or far side of the Vela SNR.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Deep-Learning Electron Diffractive Imaging

Here, we report the development of deep-learning coherent electron diffractive imaging at subangstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying the trained CNNs to recover the phase images from electron diffraction patterns of twisted hexagonal boron nitride, monolayer graphene, and a gold nanoparticle with comparable quality to those reconstructed by a conventional ptychographic algorithm. Fourier ring correlation between the CNN and ptychographic images indicates the achievement of a resolution in the range of 0.70 and 0.55 Å. We further develop CNNs to recover the probe function from the experimental data. The ability to replace iterative algorithms with CNNs and perform real-time atomic imaging from coherent diffraction patterns is expected to find applications in the physical and biological sciences.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Survey of Image Denoising Methods for Medical Image Classification

Medical imaging devices, such as X-ray machines, inherently produce images that suffer from visual noise. Our objectives were to (i.) determine the effect of image denoising on a medical image classification task, and (ii.) determine if there exists a correlation between image denoising performance and medical image classification performance. We performed the medical image classification task on chest X-rays using the DenseNet-121 convolutional neural network (CNN) and used the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics as the image denoising performance measures. We first found that different denoising methods can make a statistically significant difference in classification performance for select labels. We also found that denoising methods affect fine-tuned models more than randomly-initialized models and that fine-tuned models have significantly higher and more uniform performance than randomly-initialized models. Lastly, we found that there is no significant correlation between PSNR and SSIM values and classification performance for our task.

Michael, Peter↗

DOE OSTI2014

Task-based strategy for optimized contrast enhanced breast imaging: Analysis of six imaging techniques for mammography and tomosynthesis

Purpose: The use of contrast agents in breast imaging has the capability of enhancing nodule detectability and providing physiological information. Accordingly, there has been a growing trend toward using iodine as a contrast medium in digital mammography (DM) and digital breast tomosynthesis (DBT). Widespread use raises concerns about the best way to use iodine in DM and DBT, and thus a comparison is necessary to evaluate typical iodine-enhanced imaging methods. This study used a task-based observer model to determine the optimal imaging approach by analyzing six imaging paradigms in terms of their ability to resolve iodine at a given dose: unsubtracted mammography and tomosynthesis, temporal subtraction mammography and tomosynthesis, and dual energy subtraction mammography and tomosynthesis. Methods: Imaging performance was characterized using a detectability index d{sup ′}, derived from the system task transfer function (TTF), an imaging task, iodine signal difference, and the noise power spectrum (NPS). The task modeled a 10 mm diameter lesion containing iodine concentrations between 2.1 mg/cc and 8.6 mg/cc. TTF was obtained using an edge phantom, and the NPS was measured over several exposure levels, energies, and target-filter combinations. Using a structured CIRS phantom, d{sup ′} was generated as a function of dose and iodine concentration. Results: For all iodine concentrations and dose, temporal subtraction techniques for mammography and tomosynthesis yielded the highest d{sup ′}, while dual energy techniques for both modalities demonstrated the next best performance. Unsubtracted imaging resulted in the lowest d{sup ′} values for both modalities, with unsubtracted mammography performing the worst out of all six paradigms. Conclusions: At any dose, temporal subtraction imaging provides the greatest detectability, with temporally subtracted DBT performing the highest. The authors attribute the successful performance to excellent cancellation of inplane structures and improved signal difference in the lesion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

TU-F-18C-02: Increasing Amorphous Selenium Thickness in Direct Conversion Flat-Panel Imagers for Contrast-Enhanced Dual-Energy Breast Imaging

Purpose: Contrast-enhanced (CE) breast imaging using iodinated contrast agents requires imaging with x-ray spectra at energies greater than those used in mammography. Optimizing amorphous selenium (a-Se) flat panel imagers (FPI) for this higher energy range may increase lesion conspicuity. Methods: We compare imaging performance of a conventional FPI with 200 μm a-Se conversion layer to a prototype FPI with 300 μm a-Se layer. Both detectors are evaluated in a Siemens MAMMOMAT Inspiration prototype digital breast tomosynthesis (DBT) system using low-energy (W/Rh 28 kVp) and high-energy (W/Cu 49 kVp) x-ray spectra. Detectability of iodinated lesions in dual-energy images is evaluated using an iodine contrast phantom. Effects of beam obliquity are investigated in projection and reconstructed images using different reconstruction methods. The ideal observer signal-to-noise ratio is used as a figure-of-merit to predict the optimal a-Se thickness for CE lesion detectability without compromising conventional full-field digital mammography (FFDM) and DBT performance. Results: Increasing a-Se thickness from 200 μm to 300 μm preserves imaging performance at typical mammographic energies (e.g. W/Rh 28 kVp), and improves the detective quantum efficiency (DQE) for high energy (W/Cu 49 kVp) by 30%. While the more penetrating high-energy x-ray photons increase geometric blur due to beam obliquity in the FPI with thicker a-Se layer, the effect on lesion detectability in FBP reconstructions is negligible due to the reconstruction filters employed. Ideal observer SNR for CE objects shows improvements in in-plane detectability with increasing a-Se thicknesses, though small lesion detectability begins to degrade in oblique projections for a-Se thickness above 500 μm. Conclusion: Increasing a-Se thickness in direct conversion FPI from 200 μm to 300 μm improves lesion detectability in CE breast imaging with virtually no cost to conventional FFDM and DBT. This work was partially supported by a research grant from Siemens Healthcare.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

TH-C-18A-06: Combined CT Image Quality and Radiation Dose Monitoring Program Based On Patient Data to Assess Consistency of Clinical Imaging Across Scanner Models

Purpose: One of the principal challenges of clinical imaging is to achieve an ideal balance between image quality and radiation dose across multiple CT models. The number of scanners and protocols at large medical centers necessitates an automated quality assurance program to facilitate this objective. Therefore, the goal of this work was to implement an automated CT image quality and radiation dose monitoring program based on actual patient data and to use this program to assess consistency of protocols across CT scanner models. Methods: Patient CT scans are routed to a HIPPA compliant quality assurance server. CTDI, extracted using optical character recognition, and patient size, measured from the localizers, are used to calculate SSDE. A previously validated noise measurement algorithm determines the noise in uniform areas of the image across the scanned anatomy to generate a global noise level (GNL). Using this program, 2358 abdominopelvic scans acquired on three commercial CT scanners were analyzed. Median SSDE and GNL were compared across scanner models and trends in SSDE and GNL with patient size were used to determine the impact of differing automatic exposure control (AEC) algorithms. Results: There was a significant difference in both SSDE and GNL across scanner models (9–33% and 15–35% for SSDE and GNL, respectively). Adjusting all protocols to achieve the same image noise would reduce patient dose by 27–45% depending on scanner model. Additionally, differences in AEC methodologies across vendors resulted in disparate relationships of SSDE and GNL with patient size. Conclusion: The difference in noise across scanner models indicates that protocols are not optimally matched to achieve consistent image quality. Our results indicated substantial possibility for dose reduction while achieving more consistent image appearance. Finally, the difference in AEC methodologies suggests the need for size-specific CT protocols to minimize variability in image quality across CT vendors.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

To image, or not to image: class-specific diffractive cameras with all-optical erasure of undesired objects

Abstract Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing problem by, e.g., encrypting camera images or obscuring/blurring the imaged information through digital algorithms. Here, we demonstrate a camera design that performs class-specific imaging of target objects with instantaneous all-optical erasure of other classes of objects. This diffractive camera consists of transmissive surfaces structured using deep learning to perform selective imaging of target classes of objects positioned at its input field-of-view. After their fabrication, the thin diffractive layers collectively perform optical mode filtering to accurately form images of the objects that belong to a target data class or group of classes, while instantaneously erasing objects of the other data classes at the output field-of-view. Using the same framework, we also demonstrate the design of class-specific permutation and class-specific linear transformation cameras, where the objects of a target data class are pixel-wise permuted or linearly transformed following an arbitrarily selected transformation matrix for all-optical class-specific encryption, while the other classes of objects are irreversibly erased from the output image. The success of class-specific diffractive cameras was experimentally demonstrated using terahertz (THz) waves and 3D-printed diffractive layers that selectively imaged only one class of the MNIST handwritten digit dataset, all-optically erasing the other handwritten digits. This diffractive camera design can be scaled to different parts of the electromagnetic spectrum, including, e.g., the visible and infrared wavelengths, to provide transformative opportunities for privacy-preserving digital cameras and task-specific data-efficient imaging.

47 OTHER INSTRUMENTATION↗