X-ray-induced acoustic computed tomography of concrete infrastructure

Tang, Shanshan; Ramseyer, Chris; Samant, Pratik; Xiang, Liangzhong

doi:10.1063/1.5009936

Cited by 20 publications

(16 citation statements)

References 40 publications

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“…The most commonly used NDT methods and techniques [12] are optical NDT [13], ultrasonic NDT [14], acoustic emission testing [15], radiographic NDT [16][17][18], eddycurrent testing [19], electromagnetic NDT [20], laser systems [21], sclerometric [22] and thermographic [23] methods for evaluating the durability of concrete structures by contact and non-contact. Figure 3 shows the main NDT techniques for concrete structures.…”

Section: Ndt Methodsmentioning

confidence: 99%

Concrete Cracks Detection and Monitoring Using Deep Learning-Based Multiresolution Analysis

et al. 2021

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In this paper, we propose a new methodology for crack detection and monitoring in concrete structures. This approach is based on a multiresolution analysis of a sample or a specimen of concrete material subjected to several types of solicitation. The image obtained by ultrasonic investigation and processed by a customized wavelet is analyzed at various scales in order to detect internal cracks and crack initiation. The ultimate objective of this work is to propose an automatic crack type identification scheme based on convolutional neural networks (CNN). In this context, crack propagation can be monitored without access to the concrete surface and the goal is to detect cracks before they are visible. This is achieved through the combination of two major data analysis tools which are wavelets and deep learning. This original procedure is shown to yield a high accuracy close to 90%. In order to evaluate the performance of the proposed CNN architectures, we also used an open access database, SDNET2018, for the automatic detection of external cracks.

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Section: Ndt Methodsmentioning

confidence: 99%

Concrete Cracks Detection and Monitoring Using Deep Learning-Based Multiresolution Analysis

et al. 2021

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“…The most commonly used NDT methods and techniques [10] are optical NDT [11], ultrasonic NDT [12], acoustic emission testing [13], radiographic NDT [14,15,16], eddycurrent testing [17], electromagnetic NDT [18], laser systems [19], sclerometric [20] and thermographic [21] methods for evaluating the durability of concrete structures by contact and non-contact. Figure3 shows the main NDT techniques for concrete structures.…”

Section: Ndt Methodsmentioning

confidence: 99%

Concrete Cracks Monitoring using Deep Learning-based Multiresolution Analysis

Arbaoui¹,

Ouahabi²,

Jacques³

et al. 2021

Preprint

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In this paper, we propose a new methodology for crack monitoring in concrete structures. This approach is based on a n this paper, we propose a new methodology for monitoring cracks in concrete structures. This approach is based on a multi-resolution analysis of a sample or a specimen of the studied material subjected to several types of solicitation. The image obtained by ultrasonic investigation and processing by a dedicated wavelet will be analyzed according to several scales in order to detect internal cracks and crack initiation. The ultimate goal of this work is to propose an automatic crack type identification scheme based on convolutional neural networks (CNN). In this context, crack propagation can be monitored without access to the concrete surface and the goal is to detect cracks before they are visible on the concrete surface. The key idea allowing such a performance is the combination of two major data analysis tools which are wavelets and Deep Learning. This original procedure allows to reach a high accuracy close to 0.90. In this work, we have also implemented another approach for automatic detection of external cracks by deep learning from publicly available datasets.

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“…[33][34][35][36] In XACT imaging, X-ray-induced acoustics (XA) waves generated by an incident X-ray source spherically propagate from an X-ray absorber, therefore encoding 3D X-ray absorption information in the generated acoustic signal. [37][38][39][40][41][42][43][44][45] XACT imaging has already been proposed for in vivo dosimetry during radiation therapy, 32,33,46 breast imaging, 40 and even for nondestructive testing in industry. 41,42 However, no research has been done to apply XACT imaging on osteoporotic imaging so far.…”

Section: Introductionmentioning

confidence: 99%

The feasibility study of XACT imaging for characterizing osteoporosis

Samant

Cochran

et al. 2022

Medical Physics

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Background Osteoporosis is a progressive bone disease that is characterized by a decrease in bone mass and the deterioration in bone microarchitecture, which might be related to age and space travel. An unmet need exists for the development of novel imaging technologies to characterize osteoporosis. Purpose The purpose of our study is to investigate the feasibility of X‐ray‐induced acoustic computed tomography (XACT) imaging for osteoporosis detection. Methods An in‐house simulation workflow was developed to assess the ability of XACT for osteoporosis detection. To evaluate this simulation workflow, a three‐dimensional digital bone phantom for XACT imaging was created by a series of two‐dimensional micro‐computed tomography (micro‐CT) slices of normal and osteoporotic bones in mice. In XACT imaging, the initial acoustic pressure rise caused by the X‐ray induce acoustic (XA) effect is proportional to bone density. First, region growing was deployed for image segmentation of different materials inside the bone. Then k‐wave simulations were deployed to model XA wave propagation, attenuation, and detection. Finally, the time‐varying pressure signals detected at each transducer location were used to reconstruct the XACT image with a time‐reversal reconstruction algorithm. Results Through the simulated XACT images, cortical porosity has been calculated, and XA signal spectra slopes have been analyzed for the detection of osteoporosis. The results have demonstrated that osteoporotic bones have lower bone mineral density and higher spectra slopes. These findings from XACT images were in good agreement with porosity calculation from micro‐CT images. Conclusion This work explores the feasibility of using XACT imaging as a new imaging tool for Osteoporosis detection. Considering that acoustic signals are generated by X‐ray absorption, XACT imaging can be combined with traditional X‐ray imaging that holds potential for clinical management of osteoporosis and other bone diseases.

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X-ray-induced acoustic computed tomography of concrete infrastructure

Cited by 20 publications

References 40 publications

Concrete Cracks Detection and Monitoring Using Deep Learning-Based Multiresolution Analysis

Concrete Cracks Detection and Monitoring Using Deep Learning-Based Multiresolution Analysis

Concrete Cracks Monitoring using Deep Learning-based Multiresolution Analysis

The feasibility study of XACT imaging for characterizing osteoporosis

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