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At least 145 records · Page 8

Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks

Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help physicians distinguish diseases, an automatic organ segmentation framework is presented. The framework utilized convolution neural networks (CNN) to classify pixels. To reduce the redundant inputs, the simple linear iterative clustering (SLIC) of super-pixels and the support vector machine (SVM) classifier are introduced. To establish the perfect boundary of organs in one-pixel-level, the pixels need to be classified step-by-step. First, the SLIC is used to cut an image into grids and extract respective digital signatures. Next, the signature is classified by the SVM, and the rough edges are acquired. Finally, a precise boundary is obtained by the CNN, which is based on patches around each pixel-point. The framework is applied to abdominal CT scans of livers and high-resolution computed tomography (HRCT) scans of lungs. The experimental CT scans are derived from two public datasets (Sliver 07 and a Chinese local dataset). Experimental results show that the proposed method can precisely and efficiently detect the organs. This method consumes 38 s/slice for liver segmentation. The Dice coefficient of the liver segmentation results reaches to 97.43%. For lung segmentation, the Dice coefficient is 97.93%. This finding demonstrates that the proposed framework is a favorable method for lung segmentation of HRCT scans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The pixel tracking telescope at the Fermilab Test Beam Facility

An all silicon pixel telescope has been assembled and used at the Fermilab Test Beam Facility (FTBF) since 2009 to provide precise tracking information for different test beam experiments with a wide range of Detectors Under Test (DUTs) requiring high resolution measurement of the track impact point. The telescope is based on CMS pixel modules left over from the CMS forward pixel production. Eight planes are arranged to achieve a resolution of less than 8 μm on the 120 GeV proton beam transverse coordinate at the DUT position. In order to achieve such resolution with 100 × 150 μm 2 pixel cells, the planes were tilted to 25 degrees to maximize charge sharing between pixels. Crucial for obtaining this performance is the alignment software, called Monicelli, specifically designed and optimized for this system. This paper will describe the telescope hardware, the data acquisition system and the alignment software constituting this particle tracking system for test beam users.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unsupervised Learning for Improved Gamma-Ray Spectrometry in Pixelated Cadmium Zinc Telluride (CZT) Detectors

Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. Here, in this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154 Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The DAQ and control system for the CMS Phase-1 pixel detector upgrade

In 2017 a new pixel detector was installed in the CMS detector. This so-called Phase-1 pixel detector features four barrel layers in the central region and three disks per end in the forward regions. The upgraded pixel detector requires an upgraded data acquisition (DAQ) system to accept a new data format and larger event sizes. A new DAQ and control system has been developed based on a combination of custom and commercial microTCA parts. Custom mezzanine cards on standard carrier cards provide a front-end driver for readout, and two types of front-end controller for configuration and the distribution of clock and trigger signals. Before the installation of the detector the DAQ system underwent a series of integration tests, including readout of the pilot pixel detector, which was constructed with prototype Phase-1 electronics and operated in CMS from 2015 to 2016, quality assurance of the CMS Phase-1 detector during its assembly, and testing with the CMS Central DAQ. This paper describes the Phase-1 pixel DAQ and control system, along with the integration tests and results. A description of the operational experience and performance in data taking is included.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Sensor response and radiation damage effects for 3D pixels in the ATLAS IBL Detector

Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of ≃ 235 fb -1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 10 14 1 MeV neutron-equivalent cm -2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation

47 OTHER INSTRUMENTATION↗

First constraints on a pixelated universe in light of DESI observations

Pixelated dark energy is a string theory scenario with a quantum mechanically stable cosmological constant. The number of pixels that make up the universe slowly increases, manifesting as a time-dependent source of dark energy. DESI has recently reported evidence for dynamical dark energy that fits within this framework. In light of this, we perform the first cosmological analysis of the pixelated model. We find that the simplest model where the pixel growth rate is constant is able to accommodate the data, providing a marginally better fit than Λ⁢ CDM; and we show that models where the pixel growth rate is increasing and of order the Hubble constant today could provide better fits. Our analysis helps to clarify the features of UV constructions of dark energy necessary to accommodate the data.

dark energy↗

SU-F-J-177: A Novel Image Analysis Technique (center Pixel Method) to Quantify End-To-End Tests

Purpose: To implement a novel image analysis technique, “center pixel method”, to quantify end-to-end tests accuracy of a frameless, image guided stereotactic radiosurgery system. Methods: The localization accuracy was determined by delivering radiation to an end-to-end prototype phantom. The phantom was scanned with 0.8 mm slice thickness. The treatment isocenter was placed at the center of the phantom. In the treatment room, CBCT images of the phantom (kVp=77, mAs=1022, slice thickness 1 mm) were acquired to register to the reference CT images. 6D couch correction were applied based on the registration results. Electronic Portal Imaging Device (EPID)-based Winston Lutz (WL) tests were performed to quantify the errors of the targeting accuracy of the system at 15 combinations of gantry, collimator and couch positions. The images were analyzed using two different methods. a) The classic method. The deviation was calculated by measuring the radial distance between the center of the central BB and the full width at half maximum of the radiation field. b) The center pixel method. Since the imager projection offset from the treatment isocenter was known from the IsoCal calibration, the deviation was determined between the center of the BB and the central pixel of the imager panel. Results: Using the automatic registration method to localize the phantom and the classic method of measuring the deviation of the BB center, the mean and standard deviation of the radial distance was 0.44 ± 0.25, 0.47 ± 0.26, and 0.43 ± 0.13 mm for the jaw, MLC and cone defined field sizes respectively. When the center pixel method was used, the mean and standard deviation was 0.32 ± 0.18, 0.32 ± 0.17, and 0.32 ± 0.19 mm respectively. Conclusion: Our results demonstrated that the center pixel method accurately analyzes the WL images to evaluate the targeting accuracy of the radiosurgery system. The work was supported by a Research Scholar Grant, RSG-15-137-01-CCE from the American Cancer Society.

60 APPLIED LIFE SCIENCES↗

RiverPIXELS: paired Landsat images and expert-labeled sediment and water pixels for a selection of rivers v1.0

RiverPIXELS contains GeoTIFFs of hand-labeled water and sediment pixels from Landsat images containing rivers. Each of the 104 labeled patches contains 256 x 256 Landsat pixels (30 meter resolution). Our aim in releasing RiverPIXELS is to provide an "off-the-shelf" training and testing dataset for building machine-learned models to automatically identify rivers from multispectral imagery. While a number of trained models and/or surface water products already exist, RiverPIXELS aims for pixel-level accuracy in order to precisely identify river boundaries in particular. Our selection of rivers is heavily Arctic, but we include tropical and temperate rivers as well. Patches are provided for the Colville (7), Indigirka (6), Kolyma (4), Ucayali (54), Waitaki (21), and Yana (12) Rivers. For each patch, all surface water pixels are labeled (1) and all in-channel sediment pixels are labeled (2). Sediments not in-channel are considered part of the land (0) class. RiverPIXELS also includes paired surface water data from the Global Surface Water dataset that may be useful as additional features in machine learning models. Each patch therefore contains four aligned GeoTIFFs: labeled, landsat, gswmo, and gswocc.

54 ENVIRONMENTAL SCIENCES↗

High Energy Micron Scale Pixel Hybrid Detector

The objective of this technology development project has been to fabricate and characterize a new X-ray area image sensor innovation designed for high efficiency detection and imaging of hard X-rays (>20 KeV) with micron scale pixel resolution. A key technology component consists of a monolithic hybrid X-ray detector built by layering an amorphous Selenium X-ray photoconductor film directly deposited on a small pitch (7.8μm) CMOS active pixel readout array. A specific goal of this work is to provide a new detector tool to researchers working with synchrotron light sources, to extend the depth of exploration into nanoscale structures, and do so cost effectively. Early generation X-ray imaging detector tools fail to provide adequate resolving power and efficiency at high energies and our innovation provides a solution. A majority of proposed phase I tasks were completed. Those tasks included, in collaboration with KA Imaging, successful fabrication of specified a-Se layers on a 1Mpixel CMOS readout array to create the direct hybrid X-ray imaging array, packaging of the imaging array, assembly of electronics into a shielded detector box, loading user interface software for camera control and image capture, and performing initial (no X-ray) detector evaluation at Farrier Microengineering facilities. After initial tests, extensive testing using the X-ray beam line 1-BM source at Argonne National Laboratory Advanced Photon Source(ANL-APS) was performed. Imaging performance studies were conducted at multiple X-ray beam energies. Studies included X-ray response vs. X-ray energy, vs. applied detector field strength (HV), response linearity vs. integration time, MTF vs. beam energy, image lag measurements, and micron scale resolution pattern target imaging. This high energy micron scale X-ray detection technology is a first of a kind to be evaluated at the ANL-APS and is supported by Dr. Antonino Miceli, head of the detector physics group. Accomplishments include the first successful demonstration of a 1Mpix amorphous Selenium on CMOS readout direct hybrid X-ray imaging detector at a DOE sponsored National Laboratory. Modeled performance predictions were confirmed, proving micron scale resolution as well as an order of magnitude increase in conversion efficiency over conventional scintillator detector performance. A discovery of evidence of propagation-based phase contrast edge enhancement was unplanned and will be exploited in future experiments. This phase 1 technology demonstration verifies the efficacy of proposed high energy micron scale pixel X-ray hybrid a-Se imaging array products. The new detector products will cost effectively replace early generation detector technologies that currently fail to address increasing demand for tools to study nano structures and physical processes at high X-ray energies above 20keV. For example, current systems for transmission X-ray microscopy have low efficiency and available large pixel (~55µm) direct detectors do not offer sufficient resolution for Bragg fringe imaging at high energies. This detector innovation will solve these inadequacies. The new detector technology will compete in a $50M scientific X-ray detector market, growing at 6%, and will benefit Microtomography(µCT), X-ray diffractometry (XRD), Coherent Diffraction Imaging (CDI) applications. One application specified by Dr. Miceli at ANL is the 3D reconstruction of compact crystals at high energies requires small pixel high efficiency X-ray detectors. Farrier Microengineering, working with colleagues at KA Imaging and the University of Waterloo, successfully achieved the critical objectives of the Phase I proposal. We have proven the technical feasibility of this innovation by building and successfully testing a 1Mpixel a-Se/CMOS hybrid direct X-ray imaging array. Our commercialization roadmap of detector products will be implemented during a phase II project. We will demonstrate a migration of the technology to larger detector array sizes, improved temporal performance with detector layer engineering, and improved environmental and operational stability. Manufacturability and cost effectiveness are key objectives and product designs will leverage current state of the art CMOS wafer fabrication quality and volume manufacturing economics.

36 MATERIALS SCIENCE↗

Equalizing the Pixel Response of the Imaging Photoelectric Polarimeter Onboard the IXPE Mission

The Gas Pixel Detector is a gas detector, sensitive to the polarization of X-rays, currently flying onboard the Imaging X-ray Polarimetry Explorer (IXPE)—the first observatory dedicated to X-ray polarimetry. It detects X-rays and their polarization by imaging the ionization tracks generated by photoelectrons absorbed in the sensitive volume, and then reconstructing the initial direction of the photoelectrons. The primary ionization charge is multiplied and ultimately collected on a finely pixellated ASIC specifically developed for X-ray polarimetry. The signal of individual pixels is processed independently and gain variations can be substantial, of the order of 20%. Such variations need to be equalized to correctly reconstruct the track shape, and therefore its polarization direction. The method to do such equalization is presented here and is based on the comparison between the mean charge of a pixel with respect to the other pixels for equivalent events. The method is shown to finely equalize the response of the detectors onboard IXPE, allowing a better track reconstruction and energy resolution, and can in principle be applied to any imaging detector based on tracks.

79 ASTRONOMY AND ASTROPHYSICS↗

Methods of editing cloud and atmospheric layer affected pixels from satellite data

The location and migration of cloud, land and water features were examined in spectral space (reflective VIS vs. emissive IR). Daytime HCMM data showed two distinct types of cloud affected pixels in the south Texas test area. High altitude cirrus and/or cirrostratus and "subvisible cirrus" (SCi) reflected the same or only slightly more than land features. In the emissive band, the digital counts ranged from 1 to over 75 and overlapped land features. Pixels consisting of cumulus clouds, or of mixed cumulus and landscape, clustered in a different area of spectral space than the high altitude cloud pixels. Cumulus affected pixels were more reflective than land and water pixels. In August the high altitude clouds and SCi were more emissive than similar clouds were in July. Four-channel TIROS-N data were examined with the objective of developing a multispectral screening technique for removing SCi contaminated data.

Nixon, P. R.↗

Detection and evaluation of mixed pixels in Landsat agricultural scenes

A major problem area encountered in the identification and estimation of agricultural crop proportions in Landsat imagery involves the large proportion of the pixels which are mixed pixels, whose spectral response is influenced by more than one ground cover type. The development of methods for the detection and estimation of crop proportions in mixed pixels is presently reported. The procedure designated CASCADE, based on the estimation of the gradient image for the detection of mixed pixels, considers the consequences of a linear mixing model and is found to provide a method for the allocation of mixed pixels to the surrounding homogeneous region.

Merickel, M. B.↗

Time dependency of temperature of a laser-irradiated infrared target pixel as a low-pass filter

The thermal response of a surface layer of a pixel on an infrared target simulator is discussed. This pixel is maintained at a constant temperature by a rapidly scanning laser beam. An analytical model has been developed to describe the exact temperature dependence of a pixel as a function of time for different pixel refresh rates. The top layer of the pixel surface that generates the gray-body radiation shows the temperature dependence on time that is characteristic of a low-pass filter. The experimental results agree with the analytical predictions. The application of a pulsed laser beam to a noncontact, nondestructive diagnostic technique of surface characterization for the presence of microdefects is discussed.

Scholl, Marija S.↗

Active-Pixel Image Sensor With Analog-To-Digital Converters

Proposed single-chip integrated-circuit image sensor contains 128 x 128 array of active pixel sensors at 50-micrometer pitch. Output terminals of all pixels in each given column connected to analog-to-digital (A/D) converter located at bottom of column. Pixels scanned in semiparallel fashion, one row at time; during time allocated to scanning row, outputs of all active pixel sensors in row fed to respective A/D converters. Design of chip based on complementary metal oxide semiconductor (CMOS) technology, and individual circuit elements fabricated according to 2-micrometer CMOS design rules. Active pixel sensors designed to operate at video rate of 30 frames/second, even at low light levels. A/D scheme based on first-order Sigma-Delta modulation.

Fossum, Eric R.↗

Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

Fang, Wai-Chi↗

Preliminary Results from Small-Pixel CdZnTe and CdTe Arrays

We have evaluated 2 small-pixel (0.75 mm) Cadmium-Zinc-Telluride arrays, and one Cadmium-Telluride array, all fabricated for MSFC by Metorex (Finland) and Baltic Science Institute (Riga, Latvia). Each array was optimized for operating temperature and collection bias. It was then exposed to Cadmium-109 and Iron-55 laboratory isotopes, to measure the energy resolution for each pixel and was then scanned with a finely-collimated x-ray beam, of width 50 micron, to examine pixel to pixel and inter-pixel charge collections efficiency. Preliminary results from these array tests will be presented.

Ramsey, B. D.↗

Alternative Optimizations of X-ray TES Arrays: Soft X-rays, High Count Rates, and Mixed-Pixel Arrays

We are developing arrays of superconducting transition-edge sensors (TES) for imaging spectroscopy telescopes such as the XMS on Constellation-X. While our primary focus has been on arrays that meet the XMS requirements (of which, foremost, is an energy resolution of 2.5 eV at 6 keV and a bandpass from approx. 0.3 keV to 12 keV), we have also investigated other optimizations that might be used to extend the XMS capabilities. In one of these optimizations, improved resolution below 1 keV is achieved by reducing the heat capacity. Such pixels can be based on our XMS-style TES's with the separate absorbers omitted. These pixels can added to an array with broadband response either as a separate array or interspersed, depending on other factors that include telescope design and science requirements. In one version of this approach, we have designed and fabricated a composite array of low-energy and broad-band pixels to provide high spectral resolving power over a broader energy bandpass than could be obtained with a single TES design. The array consists of alternating pixels with and without overhanging absorbers. To explore optimizations for higher count rates, we are also optimizing the design and operating temperature of pixels that are coupled to a solid substrate. We will present the performance of these variations and discuss other optimizations that could be used to enhance the XMS or enable other astrophysics experiments.

Kilbourne, C. A.↗

GaAs QWIP Array Containing More Than a Million Pixels

A 1,024 x 1,024-pixel array of quantum-well infrared photodetectors (QWIPs) has been built on a 1.8 x 1.8- cm GaAs chip. In tests, the array was found to perform well in detecting images at wavelengths from 8 to 9 m in operation at temperatures between 60 and 70 K. The largest-format QWIP prior array that performed successfully in tests contained 512 x 640 pixels. There is continuing development effort directed toward satisfying actual and anticipated demands to increase numbers of pixels and pixel sizes in order to increase the imaging resolution of infrared photodetector arrays. A 1,024 x 1,024-pixel and even larger formats have been achieved in the InSb and HgCdTe material systems, but photodetector arrays in these material systems are very expensive and manufactured by fewer than half a dozen large companies. In contrast, GaAs-photodetector-array technology is very mature, and photodetectors in the GaAs material system can be readily manufactured by a wide range of industrial technologists, by universities, and government laboratories. There is much similarity between processing in the GaAs industry and processing in the pervasive silicon industry. With respect to yield and cost, the performance of GaAs technology substantially exceeds that of InSb and HgCdTe technologies. In addition, GaAs detectors can be designed to respond to any portion of the wavelength range from 3 to about 16 micrometers - a feature that is very desirable for infrared imaging. GaAs QWIP arrays, like the present one, have potential for use as imaging sensors in infrared measuring instruments, infrared medical imaging systems, and infrared cameras.

Jhabvala, Murzy↗