scholarly journals Machine Learning and Deterministic Approach to the Reflective Ultrasound Tomography

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7549
Author(s):  
Dariusz Majerek ◽  
Tomasz Rymarczyk ◽  
Dariusz Wójcik ◽  
Edward Kozłowski ◽  
Magda Rzemieniak ◽  
...  
Keyword(s):  
High Resolution ◽  
Complete Solution ◽  
Low Noise ◽  
Gradient Boosting ◽  
Ultrasound Tomography ◽  
Non Invasive ◽  
Extreme Gradient Boosting ◽  
High Resolution Images ◽  
Resolution Imaging ◽  
Monitoring And Diagnostics

This paper describes the method developed using the Extreme Gradient Boosting (Xgboost) algorithm that allows high-resolution imaging using the ultrasound tomography (UST) signal. More precisely, we can locate, isolate, and use the reflective peaks from the UST signal to achieve high-resolution images with low noise, which are far more useful for the location of points where the reflection occurred inside the experimental tank. Each reconstruction is divided into two parts, estimation of starting points of wave packets of raw signal (SAT—starting arrival time) and image reconstruction via XGBoost algorithm based on SAT matrix. This technology is the basis of a project to design non-invasive monitoring and diagnostics of technological processes. In this paper, we present a method of the complete solution for monitoring industrial processes. The measurements used in the study were obtained with the author’s solution of ultrasound tomography.

Principle and practice of high-resolution imaging with a field-emission TEM

1992 ◽  
Vol 50 (1) ◽  
pp. 138-139
Author(s):  
Max T. Otten ◽  
Wim M.J. Coene
Keyword(s):  
High Resolution ◽  
Field Emission ◽  
Incidence Angle ◽  
Temporal Coherence ◽  
Energy Spread ◽  
High Resolution Imaging ◽  
Major Improvement ◽  
High Resolution Images ◽  
Resolution Imaging

High-resolution imaging with a LaB6 instrument is limited by the spatial and temporal coherence, with little contrast remaining beyond the point resolution. A Field Emission Gun (FEG) reduces the incidence angle by a factor 5 to 10 and the energy spread by 2 to 3. Since the incidence angle is the dominant limitation for LaB6 the FEG provides a major improvement in contrast transfer, reducing the information limit to roughly one half of the point resolution. The strong improvement, predicted from high-resolution theory, can be seen readily in diffractograms (Fig. 1) and high-resolution images (Fig. 2). Even if the information in the image is limited deliberately to the point resolution by using an objective aperture, the improved contrast transfer close to the point resolution (Fig. 1) is already worthwhile.

High-Resolution Imaging of the Ocean Surface Backscatter by Inversion of Altimeter Waveforms

2011 ◽  
Vol 28 (8) ◽  
pp. 1050-1062 ◽  
Author(s):  
Jean Tournadre ◽  
Bertrand Chapron ◽  
Nicolas Reul
Keyword(s):  
High Resolution ◽  
Significant Wave Height ◽  
Basic Assumption ◽  
Sea Surface ◽  
Small Scale ◽  
High Resolution Imaging ◽  
Small Islands ◽  
Backscatter Coefficient ◽  
High Resolution Images ◽  
Resolution Imaging

Abstract This paper presents a new method to analyze high-resolution altimeter waveforms in terms of surface backscatter. Over the ocean, a basic assumption of modeling altimeter echo waveforms is to consider a homogeneous sea surface within the altimeter footprint that can be described by a mean backscatter coefficient. When the surface backscatter varies strongly at scales smaller than the altimeter footprint size, such as in the presence of surface slicks, rain, small islands, and altimeter echoes can be interpreted as high-resolution images of the surface whose geometry is annular and not rectangular. A method based on the computation of the imaging matrix and its pseudoinverse to infer the surface backscatter at high resolution (~300 m) from the measured waveforms is presented. The method is tested using synthetic waveforms for different surface backscatter fields and is shown to be unbiased and accurate. Several applications can be foreseen to refine the analysis of rain patterns, surface slicks, and lake surfaces. The authors choose here to focus on the small-scale variability of backscatter induced by a submerged reef smaller than the altimeter footprint as the function of tide, significant wave height, and wind.

scholarly journals Detection Capability Verification and Performance Test for the High Resolution Imaging Camera of China’s Tianwen-1 Mission

2021 ◽  
Vol 217 (6) ◽  
Author(s):  
Wei Yan ◽  
Jianjun Liu ◽  
Xin Ren ◽  
Chunlai Li ◽  
Qiang Fu ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Processing ◽  
High Resolution Imaging ◽  
Martian Surface ◽  
Detection Capability ◽  
High Quality ◽  
Mars Exploration ◽  
Imaging Camera ◽  
High Resolution Images ◽  
Resolution Imaging

AbstractHigh-resolution optical cameras have always been important scientific payloads in Mars exploration missions, which can obtain detailed images of Martian surface for the study of geomorphology, topography and geological structure. At present, there are still many challenges for Mars high-resolution images in terms of global coverage, stereo coverage (especially for colour images), and data processing methods. High Resolution Imaging Camera (HiRIC) is a high-quality, multi-mode, multi-functional, multi-spectral remote sensing camera that is suitable for the deep space developed for China’s first Mars Exploration Mission (Tianwen-1), which was successfully launched in July 2020. Here we design special experiments based on the in-orbit detection conditions of Tianwen-1 mission to comprehensively verify the detection capability and the performance of HiRIC, from the aspects of image motion compensation effect, focusing effect, image compression quality, and data preprocessing accuracy. The results showed that the performance status of HiRIC meets the requirements of obtaining high resolution images on the Martian surface. Furthermore, proposals for HiRIC in-orbit imaging strategy and data processing are discussed to ensure the acquisition of high-quality HiRIC images, which is expected to serve as a powerful complementation to the current Mars high-resolution images.

scholarly journals Micrometer-resolution imaging using MÖNCH: towards G2-less grating interferometry

2016 ◽  
Vol 23 (6) ◽  
pp. 1462-1473 ◽  
Author(s):  
Sebastian Cartier ◽  
Matias Kagias ◽  
Anna Bergamaschi ◽  
Zhentian Wang ◽  
Roberto Dinapoli ◽  
...  
Keyword(s):  
High Resolution ◽  
Silicon Detector ◽  
Limiting Factor ◽  
X Rays ◽  
X Ray ◽  
Charge Cloud ◽  
High Resolution Images ◽  
Resolution Imaging ◽  
Hybrid Silicon ◽  
Small Pixel

MÖNCH is a 25 µm-pitch charge-integrating detector aimed at exploring the limits of current hybrid silicon detector technology. The small pixel size makes it ideal for high-resolution imaging. With an electronic noise of about 110 eV r.m.s., it opens new perspectives for many synchrotron applications where currently the detector is the limiting factor,e.g.inelastic X-ray scattering, Laue diffraction and soft X-ray or high-resolution color imaging. Due to the small pixel pitch, the charge cloud generated by absorbed X-rays is shared between neighboring pixels for most of the photons. Therefore, at low photon fluxes, interpolation algorithms can be applied to determine the absorption position of each photon with a resolution of the order of 1 µm. In this work, the characterization results of one of the MÖNCH prototypes are presented under low-flux conditions. A custom interpolation algorithm is described and applied to the data to obtain high-resolution images. Images obtained in grating interferometry experiments without the use of the absorption grating G2are shown and discussed. Perspectives for the future developments of the MÖNCH detector are also presented.

scholarly journals Peritubular Dentin Lacks Piezoelectricity

2007 ◽  
Vol 86 (9) ◽  
pp. 908-911 ◽  
Author(s):  
S. Habelitz ◽  
B.J. Rodriguez ◽  
S.J. Marshall ◽  
G.W. Marshall ◽  
S.V. Kalinin ◽  
...  
Keyword(s):  
High Resolution ◽  
Piezoresponse Force Microscopy ◽  
Collagen Fibrils ◽  
Force Microscopy ◽  
Collagenous Tissue ◽  
Mineralized Tissues ◽  
Human Dentin ◽  
High Resolution Images ◽  
Resolution Imaging ◽  
Apatite Mineral

Dentin is a mesenchymal tissue, and, as such, is based on a collagenous matrix that is reinforced by apatite mineral. Collagen fibrils show piezoelectricity, a phenomenon that is used by piezoresponse force microscopy (PFM) to obtain high-resolution images. We applied PFM to image human dentin with 10-nm resolution, and to test the hypothesis that zones of piezoactivity, indicating the presence of collagen fibrils, can be distinguished in dentin. Piezoelectricity was observed by PFM in the dentin intertubular matrix, while the peritubular dentin remained without response. High-resolution imaging of chemically treated intertubular dentin attributed the piezoelectric effect to individual collagen fibrils that differed in the signal strength, depending on the fibril orientation. This study supports the hypothesis that peritubular dentin is a non-collagenous tissue and is thus an exception among mineralized tissues that derive from the mesenchyme.

scholarly journals High-Resolution Vegetation Mapping Using eXtreme Gradient Boosting Based on Extensive Features

2019 ◽  
Vol 11 (12) ◽  
pp. 1505 ◽  
Author(s):  
Heng Zhang ◽  
Anwar Eziz ◽  
Jian Xiao ◽  
Shengli Tao ◽  
Shaopeng Wang ◽  
...  
Keyword(s):  
New Zealand ◽  
High Resolution ◽  
Large Scale ◽  
Field Survey ◽  
Terrestrial Ecosystems ◽  
Google Earth ◽  
Gradient Boosting ◽  
Global Changes ◽  
Vegetation Map ◽  
Extreme Gradient Boosting

Accurate mapping of vegetation is a premise for conserving, managing, and sustainably using vegetation resources, especially in conditions of intensive human activities and accelerating global changes. However, it is still challenging to produce high-resolution multiclass vegetation map in high accuracy, due to the incapacity of traditional mapping techniques in distinguishing mosaic vegetation classes with subtle differences and the paucity of fieldwork data. This study created a workflow by adopting a promising classifier, extreme gradient boosting (XGBoost), to produce accurate vegetation maps of two strikingly different cases (the Dzungarian Basin in China and New Zealand) based on extensive features and abundant vegetation data. For the Dzungarian Basin, a vegetation map with seven vegetation types, 17 subtypes, and 43 associations was produced with an overall accuracy of 0.907, 0.801, and 0.748, respectively. For New Zealand, a map of 10 habitats and a map of 41 vegetation classes were produced with 0.946, and 0.703 overall accuracy, respectively. The workflow incorporating simplified field survey procedures outperformed conventional field survey and remote sensing based methods in terms of accuracy and efficiency. In addition, it opens a possibility of building large-scale, high-resolution, and timely vegetation monitoring platforms for most terrestrial ecosystems worldwide with the aid of Google Earth Engine and citizen science programs.

scholarly journals Introduction to the Joint Commission Meeting on High Resolution Imaging from the Ground

1989 ◽  
Vol 8 ◽  
pp. 545-546
Author(s):  
John Davis
Keyword(s):  
High Resolution ◽  
Angular Resolution ◽  
High Angular Resolution ◽  
High Resolution Imaging ◽  
Wide Range ◽  
High Resolution Images ◽  
Resolution Imaging ◽  
Optical Wavelengths ◽  
To Come ◽  
Very High

As a result of advances in instrumentation and techniques, from radio through to optical wavelengths, we have before us the prospect of producing very high resolution images of a wide range of objects across this entire spectral range. This prospect, and the new knowledge and discoveries that may be anticipated from it, lie behind an upsurge in interest in high resolution imaging from the ground. Several new high angular resolution instruments for radio, infrared, and optical wavelengths are expected to come into operation before the 1991 IAU General Assembly.

A NEW AND MODERN DIGNOSTIC TECHNIQUE: SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY (SS-OCT)

2013 ◽  
Vol 5 (2) ◽  
pp. 31-33
Author(s):  
Prakash Lokhande
Keyword(s):  
Optical Coherence Tomography ◽  
High Resolution ◽  
Optical Imaging ◽  
Optical Coherence ◽  
Cross Sectional ◽  
Swept Source ◽  
Non Invasive ◽  
Treatment Technologies ◽  
High Resolution Images ◽  
Swept Source Oct

ABSTRACT Innovative technique has been introduced in the field of dentistry for the purpose of diagnosis and treatment. Technologies like laser, composite curing techniques, optical imaging have been utilized in the field of dentistry. OCT(optical coherence tomography) is a recent. technique which creates cross-sectional high resolution images. SS-OCT(Swept -Source optical coherence tomography) is a variant of optical coherence tomography, which provides instant imaging with high resolution, non-invasive and ease of handling. This article provides a overview of Swept -Source OCT and its application in the field of dentistry.

scholarly journals Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Jiang Zhu ◽  
Jinxin Zheng ◽  
Longfei Li ◽  
Rui Huang ◽  
Haoyu Ren ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lymph Node ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Central Lymph Node ◽  
Node Negative ◽  
Non Invasive ◽  
Online Risk ◽  
Extreme Gradient Boosting ◽  
Central Lymph

Purpose: While there are no clear indications of whether central lymph node dissection is necessary in patients with T1-T2, non-invasive, clinically uninvolved central neck lymph nodes papillary thyroid carcinoma (PTC), this study seeks to develop and validate models for predicting the risk of central lymph node metastasis (CLNM) in these patients based on machine learning algorithms.Methods: This is a retrospective study comprising 1,271 patients with T1-T2 stage, non-invasive, and clinically node negative (cN0) PTC who underwent surgery at the Department of Endocrine and Breast Surgery of The First Affiliated Hospital of Chongqing Medical University from February 1, 2016, to December 31, 2018. We applied six machine learning (ML) algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), and Neural Network (NNET), coupled with preoperative clinical characteristics and intraoperative information to develop prediction models for CLNM. Among all the samples, 70% were randomly selected to train the models while the remaining 30% were used for validation. Indices like the area under the receiver operating characteristic (AUROC), sensitivity, specificity, and accuracy were calculated to test the models' performance.Results: The results showed that ~51.3% (652 out of 1,271) of the patients had pN1 disease. In multivariate logistic regression analyses, gender, tumor size and location, multifocality, age, and Delphian lymph node status were all independent predictors of CLNM. In predicting CLNM, six ML algorithms posted AUROC of 0.70–0.75, with the extreme gradient boosting (XGBoost) model standing out, registering 0.75. Thus, we employed the best-performing ML algorithm model and uploaded the results to a self-made online risk calculator to estimate an individual's probability of CLNM (https://jin63.shinyapps.io/ML_CLNM/).Conclusions: With the incorporation of preoperative and intraoperative risk factors, ML algorithms can achieve acceptable prediction of CLNM with Xgboost model performing the best. Our online risk calculator based on ML algorithm may help determine the optimal extent of initial surgical treatment for patients with T1-T2 stage, non-invasive, and clinically node negative PTC.

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