Image reconstruction with an adaptive threshold technique in electrical resistance tomography

Kim, Bong Seok; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn

doi:10.1088/0957-0233/22/10/104009

Cited by 26 publications

(15 citation statements)

References 17 publications

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“…The image including the conductivity information can be considered as the gray level of the image. Therefore, threshold technique that is used in image segmentation can be applied to the ERT image reconstruction problem [14]. In this paper, the threshold technique proposed by Otsu [15] is employed to separate the background elements from the elements of the multi-target regions and the threshold values for the classification criteria are determined in every reconstructed conductivity profile.…”

Section: Gauss-newton Methods With Adaptive Threshold Technique For Inmentioning

confidence: 99%

Two-phase Flow Visualization Employing Gauss-Newton Method in Microchannel

Liu

Wang

et al. 2013

TELKOMNIKA

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Section: Gauss-newton Methods With Adaptive Threshold Technique For Inmentioning

confidence: 99%

Two-phase Flow Visualization Employing Gauss-Newton Method in Microchannel

Liu

Wang

et al. 2013

TELKOMNIKA

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“…The studies involving quantitative inverse modeling for the cylindrical object using various FEM meshes [ 47 ] and improvement of sensitivity matrix for ERT [ 48 ] and ECT [ 49 ] showed interdependence of model design and accuracy of the estimations. In the study by [ 50 ], two separated phantoms of radius 2 cm were evaluated using iterative Gauss–Newton (GN) methods and segmented with the Otsu and adaptive threshold segmentation method at various iterations. Figure 2 shows the different FEM meshes generated using EIDORS [ 51 , 52 , 53 ].…”

Section: Ert Imagingmentioning

confidence: 99%

Quantitative Evaluations with 2d Electrical Resistance Tomography in the Low-Conductivity Solutions Using 3d-Printed Phantoms and Sucrose Crystal Agglomerate Assessments

Rao

Sattar

Wajman

et al. 2021

Sensors

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Crystallization is a significant procedure in the manufacturing of many pharmaceutical and solid food products. In-situ electrical resistance tomography (ERT) is a novel process analytical tool (PAT) to provide a cheap and quick way to test, visualize, and evaluate the progress of crystallization processes. In this work, the spatial accuracy of the nonconductive phantoms in low-conductivity solutions was evaluated. Gauss–Newton, linear back projection, and iterative total variation reconstruction algorithms were used to compare the phantom reconstructions for tap water, industrial-grade saturated sucrose solution, and demineralized water. A cylindrical phantom measuring 10 mm in diameter and a cross-section area of 1.5% of the total beaker area was detected at the center of the beaker. Two phantoms with a 10-mm diameter were visualized separately in noncentral locations. The quantitative evaluations were done for the phantoms with radii ranging from 10 mm to 50 mm in demineralized water. Multiple factors, such as ERT device and sensor development, Finite Element Model (FEM) mesh density and simulations, image reconstruction algorithms, number of iterations, segmentation methods, and morphological image processing methods, were discussed and analyzed to achieve spatial accuracy. The development of ERT imaging modality for the purpose of monitoring crystallization in low-conductivity solutions was performed satisfactorily.

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“…The studies involving quantitative inverse modeling for the cylindrical object using various FEM meshes [47] and improvement of sensitivity matrix for ERT [48] and ECT [49] showed interdependence of model design and accuracy of the estimations. In the study by [50], two separated phantoms of radius 2 cm were evaluated using iterative GN methods and segmented with the Otsu and adaptive threshold segmentation method at various iterations. Figure 2 shows the different FEM meshes generated using EIDORS [51][52][53].…”

Section: Modelling and Simulation Studies In Ertmentioning

confidence: 99%

Quantitative Evaluations with 2D Electrical Resistance Tomography in the Low Conductivity Solutions Using 3D Printed Phantoms for Crystallization Process Monitoring

Rao¹,

Sattar²,

Wajman³

et al. 2020

Preprint

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Crystallization is a significant procedure in the manufacturing of many pharmaceutical and solid food products. In-situ Electrical Resistance Tomography (ERT) is a novel Process Analytical Tool (PAT) to provide a cheap and quick way to test, visualize, and evaluate the progress of crystallization processes. In this work, the spatial accuracy of the non-conductive phantoms in low conductivity solutions was evaluated. Gauss-Newton, Linear Back Projection, and iterative Total Variation reconstruction algorithms were used to compare the phantom reconstructions for tap water, industrial-grade saturated sucrose solution, and demineralized water. Cylindrical phantom measuring 10 mm in diameter and a cross-section area of 1.5 % of the total beaker area was detected at the center of the beaker. Two phantoms with a 10 mm diameter were visualized separately in non-central locations. The quantitative evaluations were done for the phantoms with radii ranging from 10 mm to 50 mm in demineralized water. Multiple factors such as ERT device and sensor development, FEM mesh density and simulations, image reconstruction algorithms, number of iterations, segmentation methods, and morphological image processing methods were discussed and analyzed to achieve spatial accuracy. The development of ERT imaging modality for the purpose of monitoring crystallization in low conductivity solutions was performed satisfactorily.

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Image reconstruction with an adaptive threshold technique in electrical resistance tomography

Cited by 26 publications

References 17 publications

Two-phase Flow Visualization Employing Gauss-Newton Method in Microchannel

Two-phase Flow Visualization Employing Gauss-Newton Method in Microchannel

Quantitative Evaluations with 2d Electrical Resistance Tomography in the Low-Conductivity Solutions Using 3d-Printed Phantoms and Sucrose Crystal Agglomerate Assessments

Quantitative Evaluations with 2D Electrical Resistance Tomography in the Low Conductivity Solutions Using 3D Printed Phantoms for Crystallization Process Monitoring

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