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At least 379 records · Page 21

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗

Super Resolution Digital Image Correlation (SR-DIC): an Alternative to Image Stitching at High Magnifications

Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.

Hansen, R. S.↗

Advanced Imaging Techniques in Skull Base Osteomyelitis Due to Malignant Otitis Externa

Purpose of Review: To give an up-to-date overview of the strengths and weaknesses of current imaging modalities in diagnosis and follow-up of skull base osteomyelitis (SBO). Recent Findings: CT and MRI are both used for anatomical imaging, and nuclear techniques aid in functional process imaging. Hybrid techniques PET-CT and PET-MRI are the newest modalities which combine imaging strengths. Summary: No single modality is able to address the scope of SBO. A combination of functional and anatomical imaging is needed, in the case of newly suspected SBO we suggest the use of PET-MRI (T1, T2, T1-FS-GADO, DWI) and separate HRCT for diagnosis and follow-up.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Fractal breakage of porous carbonate sand particles: Microstructures and mechanisms

In situ, three-dimensional (3D) characterizations of particle breakage in porous carbonate sands are presented, for the first time, with synchrotron-based micro computed tomography. Evolution of grain-scale characteristics are identified and quantified via elaborate image processing and topology analyses. The sequential 3D images reveal distinctly different fracture mechanisms for carbonate sands from silica sands. The angular shape of carbonate sand particles facilitates bending fracture, and particles with a lower sphericity and a higher porosity are more prone to break. 3D crack networks extracted from fractured particles imply considerable cleavage along initial pores. The fractal dimension of crack networks increases with external loading due to crack branching via cleavage. The resultant fragment size distribution also appears fractal and the fractal feature is valid down to the breakage limit of calcium carbonate. Crack propagation along the initial pores reduces the energy barrier for particle breakage and thus fracture strength of particles

Carbonate sands↗

Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis

In this paper, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.

36 MATERIALS SCIENCE↗

Scalable pCT Image Reconstruction Delivered as a Cloud Service

We describe a cloud-based medical image reconstruction service designed to meet a real-time and daily demand to reconstruct thousands of images from proton cancer treatment facilities worldwide. Rapid reconstruction of a three-dimensional Proton Computed Tomography (pCT) image can require the transfer of 100 GB of data and use of approximately 120 GPU-enabled compute nodes. The nature of proton therapy means that demand for such a service is sporadic and comes from potentially hundreds of clients worldwide. We thus explore the use of a commercial cloud as a scalable and cost-efficient platform for pCT reconstruction. To address the high performance requirements of this application we leverage Amazon Web Services' GPU-enabled cluster resources that are provisioned with high performance networks between nodes. To support episodic demand, we develop an on-demand multi-user provisioning service that can dynamically provision and resize clusters based on image reconstruction requirements, priorities, and wait times. We compare the performance of our pCT reconstruction service running on commercial cloud resources with that of the same application on dedicated local high performance computing resources. We show that we can achieve scalable and on-demand reconstruction of large scale pCT images for simultaneous multi-client requests, processing images in less than 10 minutes for less than $10 per image.

Cloud computing↗

Data association algorithm for large-scale multi-object tracking with complex interactions

We present an online multi-object tracking algorithm to track multiple objects across a large number of image frames. Our work is motivated by the need to study evolution of nanoscale objects by transmission electron microscopy. The proposed approach is based on the existing multi-way data association tracking algorithm that is capable of tracking interacting objects with complex behaviors (i.e., merge, split, overlap, and appearance or disappearance). The multi-way data association is an offline algorithm to associate objects across all image frames at one step with a global optimization, which does not scale very well for large number of image frames. The proposed online tracking algorithm processes image frames as they arrive by detecting all objects in the newly arrived image frame and making the associations of the objects to those detected from the previous frame by the multi-way data association. This frameby-frame association scheme can cause fragmented traces of the objects that are occasionally misdetected for some image frames. We overcome this issue by allowing previously unassociated objects to be associated when the objects reappear within a fixed number of future image frames, namely the frame-delayed association. We combine the multi-way data association with the frame-delayed association to be able to track interacting objects with accurate handling of object disappearance events. The proposed method is validated through applications to simulated multi-object tracking problem and a real multi-object tracking problem. Here, the outcome of the proposed method is compared with four state-of-the-art algorithms.

36 MATERIALS SCIENCE↗

TH-E-9A-01: Medical Physics 1.0 to 2.0, Session 4: Computed Tomography, Ultrasound and Nuclear Medicine

Medical Physics 2.0 is a bold vision for an existential transition of clinical imaging physics in face of the new realities of value-based and evidencebased medicine, comparative effectiveness, and meaningful use. It speaks to how clinical imaging physics can expand beyond traditional insular models of inspection and acceptance testing, oriented toward compliance, towards team-based models of operational engagement, prospective definition and assurance of effective use, and retrospective evaluation of clinical performance. Organized into four sessions of the AAPM, this particular session focuses on three specific modalities as outlined below. CT 2.0: CT has been undergoing a dramatic transition in the last few decades. While the changes in the technology merits discussions of their own, an important question is how clinical medical physicists are expected to effectively engage with the new realities of CT technology and practice. Consistent with the upcoming paradigm of Medical Physics 2.0, this CT presentation aims to provide definitions and demonstration of the components of the new clinical medical physics practice pertaining CT. The topics covered include physics metrics and analytics that aim to provide higher order clinicallyrelevant quantification of system performance as pertains to new (and not so new) technologies. That will include the new radiation and dose metrics (SSDE, organ dose, risk indices), image quality metrology (MTF/NPS/d’), task-based phantoms, and the effect of patient size. That will follow with a discussion of the testing implication of new CT hardware (detectors, tubes), acquisition methods (innovative helical geometries, AEC, wide beam CT, dual energy, inverse geometry, application specialties), and image processing and analysis (iterative reconstructions, quantitative CT, advanced renditions). The presentation will conclude with a discussion of clinical and operational aspects of Medical Physics 2.0 including training and communication, use optimization (dose and technique factors), automated analysis and data management (automated QC methods, protocol tracking, dose monitoring, issue tracking), and meaningful QC considerations. US 2.0: Ultrasound imaging is evolving at a rapid pace, adding new imaging functions and modes that continue to enhance its clinical utility and benefits to patients. The ultrasound talk will look ahead 10–15 years and consider how medical physicists can bring maximal value to the clinical ultrasound practices of the future. The roles of physics in accreditation and regulatory compliance, image quality and exam optimization, clinical innovation, and education of staff and trainees will all be considered. A detailed examination of expected technology evolution and impact on image quality metrics will be presented. Clinical implementation of comprehensive physics services will also be discussed. Nuclear Medicine 2.0: Although the basic science of nuclear imaging has remained relatively unchanged since its inception, advances in instrumentation continue to advance the field into new territories. With a great number of these advances occurring over the past decade, the role and testing strategies of clinical nuclear medicine physicists must evolve in parallel. The Nuclear Medicine 2.0 presentation is designed to highlight some of the recent advances from a clinical medical physicist perspective and provide ideas and motivation for designing better evaluation strategies. Topics include improvement of traditional physics metrics and analytics, testing implications of hybrid imaging and advanced detector technologies, and strategies for effective implementation into the clinic. Learning Objectives: Become familiar with new physics metrics and analytics in nuclear medicine, CT, and ultrasound. To become familiar with the major new developments of clinical physics support. To understand the physics testing implications of new technologies, hardware, software, and applications. Identify approaches for implementing comprehensive medical physics services in future imaging practices.

60 APPLIED LIFE SCIENCES↗

als microct recon (microct) v1

Jupyter notebooks to reconstruct and visualize microCT data from ALS beamline 8.3.2. Relies on standard tomography and image processing tools (astra, tomopy, itk, scikit-image) and ipywidgets (sliders, drop down menus, etc) to make parameter selection and data visualization easy for users.

Parkinson, Dilworth↗

A thesis on the Development of an Automated SWIFT Edge Detection Algorithm

Throughout the world, scientists and engineers such as those at Los Alamos National Laboratory, perform research and testing unique only to applications aimed towards advancing technology, and understanding the nature of materials. With this testing, comes a need for advanced methods of data acquisition and most importantly, a means of analyzing and extracting the necessary information from such acquired data. In this thesis, I aim to produce an automated method implementing advanced image processing techniques and tools to analyze SWIFT image datasets for Detonator Technology at Los Alamos National Laboratory. Such an effective method for edge detection and point extraction can prove to be advantageous in analyzing such unique datasets and provide for consistency in producing results.

97 MATHEMATICS AND COMPUTING↗

Multi-Scale Characterization of Porosity and Cracks in Silicon Carbide Cladding after Transient Reactor Test Facility Irradiation

Silicon carbide (SiC) ceramic matrix composite (CMC) cladding is currently being pursued as one of the leading candidates for accident-tolerant fuel (ATF) cladding for light water reactor applications. The morphology of fabrication defects, including the size and shape of voids, is one of the key challenges that impacts cladding performance and guarantees reactor safety. Therefore, quantification of defects’ size, location, distribution, and leak paths is critical to determining SiC CMC in-core performance. This research aims to provide quantitative insight into the defect’s distribution under multi-scale characterization at different length scales before and after different Transient Reactor Test Facility (TREAT) irradiation tests. A non-destructive multi-scale evaluation of irradiated SiC will help to assess critical microstructural defects from production and/or experimental testing to better understand and predict overall cladding performance. X-ray computed tomography (XCT), a non-destructive, data-rich characterization technique, is combined with lower length scale electronic microscopic characterization, which provides microscale morphology and structural characterization. This paper discusses a fully automatic workflow to detect and analyze SiC-SiC defects using image processing techniques on 3D X-ray images. Following the XCT data analysis, advanced characterizations from focused ion beam (FIB) and transmission electron microscopy (TEM) were conducted to verify the findings from the XCT data, especially quantitative results from local nano-scale TEM 3D tomography data, which were utilized to complement the 3D XCT results. In this work, three SiC samples (two irradiated and one unirradiated) provided by General Atomics are investigated. The irradiated samples were irradiated in a way that was expected to induce cracking, and indeed, the automated workflow developed in this work was able to successfully identify and characterize the defects formation in the irradiated samples while detecting no observed cracking in the unirradiated sample. These results demonstrate the value of automated XCT tools to better understand the damage and damage propagation in SiC-SiC structures for nuclear applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Tobin, Jr., Kenneth William↗

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

59 BASIC BIOLOGICAL SCIENCES↗

Automatic tool alignment in a backscatter x-ray scanning system

Technologies pertaining to backscatter x-ray scanning systems are described herein. The backscatter x-ray scanning system includes an x-ray source, which directs collimated x-rays along a plurality of output vectors towards a target. A detector detects diffusely reflected x-rays subsequent to respective collimated x-rays impacting the target, and outputs signals indicative of parameters of the detected x-rays. An image processing system generates an x-ray image based upon parameters of the detected x-rays, wherein each pixel in the image corresponds to a respective output vector. A user selects a particular portion of the image, and a tool is positioned such that its directional axis is coincident with the output vector corresponding to at least one pixel in the portion of the image.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Automatic tool alignment in a backscatter X-ray scanning system

Technologies pertaining to backscatter x-ray scanning systems are described herein. The backscatter x-ray scanning system includes an x-ray source, which directs collimated x-rays along a plurality of output vectors towards a target. A detector detects diffusely reflected x-rays subsequent to respective collimated x-rays impacting the target, and outputs signals indicative of parameters of the detected x-rays. An image processing system generates an x-ray image based upon parameters of the detected x-rays, wherein each pixel in the image corresponds to a respective output vector. A user selects a particular portion of the image, and a medical device is positioned such that its directional axis is coincident with the output vector corresponding to at least one pixel in the portion of the image.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

First Steps Toward Incorporating Image Based Diagnostics Into Particle Accelerator Control Systems Using Convolutional Neural Networks

At present, a variety of image-based diagnostics are used in particle accelerator systems. Often times, these are viewed by a human operator who then makes appropriate adjustments to the machine. Given recent advances in using convolutional neural networks (CNNs) for image processing, it should be possible to use image diagnostics directly in control routines (NN-based or otherwise). This is especially appealing for non-intercepting diagnostics that could run continuously during beam operation. Here, we show results of a first step toward implementing such a controller: our trained CNN can predict multiple simulated downstream beam parameters at the Fermilab Accelerator Science and Technology (FAST) facility's low energy beamline using simulated virtual cathode laser images, gun phases, and solenoid strengths.

43 PARTICLE ACCELERATORS↗

Thermo-mechanical processing window for β phase recrystallization inTi-5Al-5Mo-5V-3Cr alloy

Highlights: • A processing window has been developed to obtain fine uniform recrystallized grains. • High deformation (90%) with annealing at intermediate temperature (950 °C) suggested • Dynamic recrystallization (Drx) should be avoided. • DRx reduces driving force for static rx. It gives bimodal distribution of grains. • Final deformation step should be in the α + β phase field. Ti-5Al-5Mo-5V-3Cr (Ti-5553) is a high strength β titanium alloy. It is now commonly used in thick section aerospace components. In general, the thermo-mechanical processing (TMP) of β titanium alloys done at high temperature to obtain uniformly recrystallized fine grain structure is one of the major challenges. Through this work, a TMP window for Ti-5553 (through systematic variation in % reduction and post deformation annealing temperature) has been developed to obtain fine uniformly recrystallized β grains. Grain size has been quantified on EBSD generated orientation maps, by applying stereological methods, image processing and automated reconstruction. Effects of % deformation and post deformation annealing temperature, as well as that of initial ingot size prior to deformation and the capacity of the forge on the static and dynamic recrystallization behavior, which eventually determine the final grain size distribution, have been illustrated.

36 MATERIALS SCIENCE↗

Applications of photogrammetry to structural assessment

Photogrammetry is a method developed in the early XIXth century. Nowadays, with digital photography associated to the development of image processing and its automation, this technique has become appealing in different fields of application. In this paper, the authors analysed the current feasibility and advantages of using photogrammetry in structural monitoring. First, the method was calibrated using two laboratorial tests: (1) monitoring of failure and creep tests of long-span reinforced concrete beams; and (2) monitoring of steel beam-to-column connections. Then, the method was tested on site, namely, in monitoring the deformations of a footbridge subjected to different loading situations. It was concluded that photogrammetry can be used in structural monitoring with accuracy and exhibiting additional advantages in relation to traditional methods, namely: (1) an almost unlimited number of measuring points can be considered and automatically processed; and (2) hardware is unnecessary and, therefore, it can be used under almost any situation where traditional methods cannot be employed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗