scholarly journals Correlations in Joint Spectral and Polarization Imaging

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 6
Author(s):  
Guillaume Courtier ◽  
Pierre-Jean Lapray ◽  
Jean-Baptiste Thomas ◽  
Ivar Farup
Keyword(s):  
Imaging Techniques ◽  
Image Data ◽  
Computational Imaging ◽  
Channel Correlation ◽  
Image Statistics ◽  
Polarization Imaging ◽  
Joint Processing ◽  
Polarization Image ◽  
Spectral Channels

Recent imaging techniques enable the joint capture of spectral and polarization image data. In order to permit the design of computational imaging techniques and future processing of this information, it is interesting to describe the related image statistics. In particular, in this article, we present observations for different correlations between spectropolarimetric channels. The analysis is performed on several publicly available databases that are unified for joint processing. We perform global investigation and analysis on several specific clusters of materials or reflection types. We observe that polarization channels generally have more inter-channel correlation than the spectral channels.

scholarly journals Current Applications, Opportunities, and Limitations of AI for 3D Imaging in Dental Research and Practice

2020 ◽  
Vol 17 (12) ◽  
pp. 4424
Author(s):  
Kuofeng Hung ◽  
Andy Wai Kan Yeung ◽  
Ray Tanaka ◽  
Michael M. Bornstein
Keyword(s):  
Treatment Planning ◽  
3D Imaging ◽  
Imaging Techniques ◽  
Current Trend ◽  
Three Dimensional ◽  
Image Data ◽  
Anatomical Landmarks ◽  
Automated Diagnosis ◽  
Dental Practitioners ◽  
Facial Scanning

The increasing use of three-dimensional (3D) imaging techniques in dental medicine has boosted the development and use of artificial intelligence (AI) systems for various clinical problems. Cone beam computed tomography (CBCT) and intraoral/facial scans are potential sources of image data to develop 3D image-based AI systems for automated diagnosis, treatment planning, and prediction of treatment outcome. This review focuses on current developments and performance of AI for 3D imaging in dentomaxillofacial radiology (DMFR) as well as intraoral and facial scanning. In DMFR, machine learning-based algorithms proposed in the literature focus on three main applications, including automated diagnosis of dental and maxillofacial diseases, localization of anatomical landmarks for orthodontic and orthognathic treatment planning, and general improvement of image quality. Automatic recognition of teeth and diagnosis of facial deformations using AI systems based on intraoral and facial scanning will very likely be a field of increased interest in the future. The review is aimed at providing dental practitioners and interested colleagues in healthcare with a comprehensive understanding of the current trend of AI developments in the field of 3D imaging in dental medicine.

Post-mortem computed tomography: Technical principles and recommended parameter settings for high-resolution imaging

2018 ◽  
Vol 58 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Dominic Gascho ◽  
Michael J. Thali ◽  
Tilo Niemann
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Imaging Techniques ◽  
Standard Procedure ◽  
Image Data ◽  
Post Mortem ◽  
Raw Data ◽  
Resolution Imaging ◽  
Technical Principles ◽  
Dose Imaging

Post-mortem computed tomography (PMCT) has become a standard procedure in many forensic institutes worldwide. However, the standard scan protocols offered by vendors are optimised for clinical radiology and its main considerations regarding computed tomography (CT), namely, radiation exposure and motion artefacts. Thus, these protocols aim at low-dose imaging and fast imaging techniques. However, these considerations are negligible in post-mortem imaging, which allows for significantly increased image quality. Therefore, the parameters have to be adjusted to achieve the best image quality. Several parameters affect the image quality differently and have to be weighed against each other to achieve the best image quality for different diagnostic interests. There are two main groups of parameters that are adjustable by the user: acquisition parameters and reconstruction parameters. Acquisition parameters have to be selected prior to scanning and affect the raw data composition. In contrast, reconstruction parameters affect the calculation of the slice stacks from the raw data. This article describes the CT principles from acquiring image data to post-processing and provides an overview of the significant parameters for increasing the image quality in PMCT. Based on the CT principles, the effects of these parameters on the contrast, noise, resolution and frequently occurring artefacts are described. This article provides a guide for the performance of PMCT in morgues, clinical facilities or private practices.

scholarly journals Survey of Demosaicking Methods for Polarization Filter Array Images

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3688 ◽  
Author(s):  
Sofiane Mihoubi ◽  
Pierre-Jean Lapray ◽  
Laurent Bigué
Keyword(s):  
Strongly Correlated ◽  
Polarization Filter ◽  
Channel Correlation ◽  
Polarization Imaging ◽  
Subjective Analysis ◽  
Filter Array ◽  
Total Polarization ◽  
Polarization States ◽  
Field Oscillation ◽  
Image Difference

Snapshot polarization imaging has gained interest in the last few decades. Recent research and technology achievements defined the polarization Filter Array (PFA). It is dedicated to division-of-focal plane polarimeters, which permits to analyze the direction of light electric field oscillation. Its filters form a mosaicked pattern, in which each pixel only senses a fraction of the total polarization states, so the other missing polarization states have to be interpolated. As for Color or Spectral Filter Arrays (CFA or SFA), several dedicated demosaicking methods exist in the PFA literature. Such methods are mainly based on spatial correlation disregarding inter-channel correlation. We show that polarization channels are strongly correlated in images. We therefore propose to extend some demosaicking methods from CFA/SFA to PFA, and compare them with those that are PFA-oriented. Objective and subjective analysis show that the pseudo panchromatic image difference method provides the best results and can be used as benchmark for PFA demosaicking.

Filtered Rayleigh Scattering Thermometry in a Premixed Sooting Flame

Volume 4 ◽  
2004 ◽  
Author(s):  
Sean P. Kearney ◽  
Thomas W. Grasser ◽  
Steven J. Beresh
Keyword(s):  
Rayleigh Scattering ◽  
Volume Fraction ◽  
Imaging Techniques ◽  
Soot Volume Fraction ◽  
Image Data ◽  
Molecular Iodine ◽  
Line Center ◽  
Temperature Imaging ◽  
Planar Laser ◽  
Laser Induced Incandescence

Filtered Rayleigh Scattering (FRS) is demonstrated in a premixed, sooting ethylene-air flame. In sooting flames, traditional laser-based temperature-imaging techniques such linear (unfiltered) Rayleigh scatting (LRS) and planar laser-induced fluorescence (PLIF) are rendered intractable due to intense elastic scattering interferences from in-flame soot. FRS partially overcomes this limitation by utilizing a molecular iodine filter in conjunction with an injection-seeded Nd:YAG laser, where the seeded laser output is tuned to line center of a strong iodine absorption transition. A significant portion of the Doppler-broadened molecular Rayleigh signal is then passed while intense soot scattering at the laser line is strongly absorbed. In this paper, we demonstrate the feasibility of FRS for sooting flame thermometry using a premixed, ethylene-air flat flame. We present filtered and unfiltered laser light-scattering images, FRS temperature data, and laser-induced incandescence (LII) measurements of soot volume fraction for fuel-air equivalence ratios of φ = 2.19 and 2.24. FRS-measured product temperatures for these flames are nominally 1500 K. The FRS temperature and image data are discussed in the context of the soot LII results and a preliminary estimate of the upper sooting limit for our FRS system of order 0.1 ppm volume fraction is obtained.

scholarly journals RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6571
Author(s):  
Timothy I. Anderson ◽  
Kelly M. Guan ◽  
Bolivia Vega ◽  
Saman A. Aryana ◽  
Anthony R. Kovscek
Keyword(s):  
Source Rock ◽  
Binary Data ◽  
Broad Class ◽  
Imaging Techniques ◽  
Image Data ◽  
Generative Models ◽  
Training Data ◽  
Grayscale Image ◽  
Flow Models ◽  
Rock Characterization

Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models have shown success, existing methods for generating 3D volumes from 2D training images are restricted to binary images and grayscale volume generation requires 3D training data. Shale characterization relies on 2D imaging techniques such as scanning electron microscopy (SEM), and grayscale values carry important information about porosity, kerogen content, and mineral composition of the shale. Here, we introduce RockFlow, a method based on generative flow models that creates grayscale volumes from 2D training data. We apply RockFlow to baseline binary micro-CT image volumes and compare performance to a previously proposed model. We also show the extension of our model to 2D grayscale data by generating grayscale image volumes from 2D SEM and dual modality nanoscale shale images. The results show that our method underestimates the porosity and surface area on the binary baseline datasets but is able to generate realistic grayscale image volumes for shales. With improved binary data preprocessing, we believe that our model is capable of generating synthetic porous media volumes for a very broad class of rocks from shale to carbonates to sandstone.

scholarly journals DIGITAL RECONSTRUCTION OF SOFT-TISSUE STRUCTURES IN FOSSILS

2016 ◽  
Vol 22 ◽  
pp. 101-117 ◽  
Author(s):  
Stephan Lautenschlager
Keyword(s):  
Soft Tissue ◽  
Soft Tissues ◽  
Imaging Techniques ◽  
Analytical Techniques ◽  
Computational Imaging ◽  
Whole Body ◽  
Element Analysis ◽  
Digital Reconstruction ◽  
New Information ◽  
Tissue Structures

AbstractIn the last two decades, advances in computational imaging techniques and digital visualization have created novel avenues for the study of fossil organisms. As a result, paleontology has undergone a shift from the pure study of physically preserved bones and teeth, and other hard tissues, to using virtual computer models to study specimens in greater detail, restore incomplete specimens, and perform biomechanical analyses. The rapidly increasing application of these techniques has further paved the way for the digital reconstruction of soft-tissue structures, which are rarely preserved or otherwise available in the fossil record. In this contribution, different types of digital soft-tissue reconstructions are introduced and reviewed. Provided examples include methodological approaches for the reconstruction of musculature, endocranial components (e.g., brain, inner ear, and neurovascular structures), and other soft tissues (e.g., whole-body and life reconstructions). Digital techniques provide versatile tools for the reconstruction of soft tissues, but given the nature of fossil specimens, some limitations and uncertainties remain. Nevertheless, digital reconstructions can provide new information, in particular if interpreted in a phylogenetically grounded framework. Combined with other digital analytical techniques (e.g., finite element analysis [FEA], multibody dynamics analysis [MDA], and computational fluid dynamics [CFD]), soft-tissue reconstructions can be used to elucidate the paleobiology of extinct organisms and to test competing evolutionary hypotheses.

Imaging Morphogenesis: Technological Advances and Biological Insights

Science ◽  
2013 ◽  
Vol 340 (6137) ◽  
pp. 1234168 ◽  
Author(s):  
Philipp J. Keller
Keyword(s):  
Structural Changes ◽  
Imaging Techniques ◽  
Spatial Scales ◽  
Image Data ◽  
Physical Models ◽  
Data Sets ◽  
Full Potential ◽  
Technological Advances ◽  
Complex Image ◽  
Underlying Mechanisms

Morphogenesis, the development of the shape of an organism, is a dynamic process on a multitude of scales, from fast subcellular rearrangements and cell movements to slow structural changes at the whole-organism level. Live-imaging approaches based on light microscopy reveal the intricate dynamics of this process and are thus indispensable for investigating the underlying mechanisms. This Review discusses emerging imaging techniques that can record morphogenesis at temporal scales from seconds to days and at spatial scales from hundreds of nanometers to several millimeters. To unlock their full potential, these methods need to be matched with new computational approaches and physical models that help convert highly complex image data sets into biological insights.

Observation of Large-Scale Structures in Unsaturated Materials

1990 ◽  
Vol 195 ◽  
Author(s):  
J. E. Maneval ◽  
M.J. Mccarthy ◽  
S. Whitaker
Keyword(s):  
Magnetic Resonance Imaging ◽  
Nuclear Magnetic Resonance ◽  
Large Scale ◽  
Imaging Techniques ◽  
Image Data ◽  
Small Scale ◽  
Resonance Imaging ◽  
Specific System ◽  
Large Scale Structures ◽  
Scale Structures

ABSTRACTWe report here the use of nuclear magnetic resonance imaging in the observation of liquid-phase fraction distributions in a partially-wetted sample of glass beads. By combiningboth large- and small-scale imaging techniques, we can study the transition from local-averaged saturations to large-scale averaged saturations. The image data allows us to assess the utility of the large-scale measurements We comment on the reliability and generality of the measurements for our specific system.

scholarly journals Digital Archiving of Civil War Graffiti for Research & Access

2021 ◽  
Vol 2021 (1) ◽  
pp. 107-112
Author(s):  
Andrea J. Loewenwarter ◽  
Margaret L. Misch ◽  
Kristin Jacobsen ◽  
Mills Kelly ◽  
Michael B. Toth
Keyword(s):  
Civil War ◽  
Multispectral Imaging ◽  
New Technologies ◽  
Imaging Techniques ◽  
Image Data ◽  
Imaging Systems ◽  
Advanced Imaging ◽  
Data Archiving ◽  
Technical Systems ◽  
Civil War Era

Historic properties face challenges preserving and maintaining their physical heritage, as well as digitally sharing and accessing their history in a virtual environment. They are now utilizing new advanced imaging methods to research their cultural heritage artifacts. Recent advanced imaging in historic Civil War-era houses demonstrated the integration of imaging techniques and data to support conservation of these structures and research into their history and contents. New technical systems, including the latest narrowband multispectral imaging systems and higher resolution cameras, raise major challenges in not only the integration of new technologies, but also the ability to store, manage and access large amounts of data. Integration, preservation, access and collaboration with the image data from this program requires implementation of standardized digitization and data archiving practices.

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