Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors

Sandro R. Fernandes; Joaquim T. de Assis; Vania Vieira Estrela; Navid Razmjooy; Anand Deshpande; P. Patavardhan; R. J. Aroma; K. Raimond; Hermes J. Loschi; Douglas A. Nascimento

doi:10.1007/978-3-030-57552-6_16

Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors

Sandro R. Fernandes, Joaquim T. de Assis, Vania Vieira Estrela, Navid Razmjooy, Anand Deshpande, P. Patavardhan, R. J. Aroma, K. Raimond, Hermes J. Loschi, Douglas A. Nascimento

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

X-ray computed microtomography (μCT or micro-CT) allows a nondestructive analysis of samples, which helps their reuse. The X-ray μCT equipment offers the user several configuration options that change the quality of the images obtained, thus affecting the expected result. In this study, a methodology for analyzing X-ray μCT images generated by the SkyScan 1174 Compact Micro-CT equipment was developed. The basis of this analysis methodology is texture descriptors. Three sets of images were used, and then degradations and noise were applied to the original images, generating new images. Subsequently, the following texture descriptors assisted in scrutinizing the sets: maximum probability, the moment of difference, the inverse difference moment, entropy, and uniformity. Experiments show the outcomes of some tests.

Original language	English
Title of host publication	Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings
Subtitle of host publication	Proceedings of the ICHSMT 2019
ISBN (Electronic)	978-3-030-57552-6
DOIs	https://doi.org/10.1007/978-3-030-57552-6_16
Publication status	Published - 2021
Externally published	Yes
Event	International Congress on Health Sciences and Medical Technologies, ICHSMT 2019 - Tlemcen, Algeria Duration: 5 Dec 2019 → 7 Dec 2019

Conference

Conference	International Congress on Health Sciences and Medical Technologies, ICHSMT 2019
Country/Territory	Algeria
City	Tlemcen
Period	5/12/19 → 7/12/19

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10.1007/978-3-030-57552-6_16

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Fernandes, S. R., Assis, J. T. D., Estrela, V. V., Razmjooy, N., Deshpande, A., Patavardhan, P., Aroma, R. J., Raimond, K., Loschi, H. J., & Nascimento, D. A. (2021). Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors. In Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings: Proceedings of the ICHSMT 2019 https://doi.org/10.1007/978-3-030-57552-6_16

@inproceedings{25dd11c58a1d4562aba4bc5ce71753fc,

title = "Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors",

abstract = "X-ray computed microtomography (μCT or micro-CT) allows a nondestructive analysis of samples, which helps their reuse. The X-ray μCT equipment offers the user several configuration options that change the quality of the images obtained, thus affecting the expected result. In this study, a methodology for analyzing X-ray μCT images generated by the SkyScan 1174 Compact Micro-CT equipment was developed. The basis of this analysis methodology is texture descriptors. Three sets of images were used, and then degradations and noise were applied to the original images, generating new images. Subsequently, the following texture descriptors assisted in scrutinizing the sets: maximum probability, the moment of difference, the inverse difference moment, entropy, and uniformity. Experiments show the outcomes of some tests.",

author = "Fernandes, {Sandro R.} and Assis, {Joaquim T. de} and Estrela, {Vania Vieira} and Navid Razmjooy and Anand Deshpande and P. Patavardhan and Aroma, {R. J.} and K. Raimond and Loschi, {Hermes J.} and Nascimento, {Douglas A.}",

year = "2021",

doi = "10.1007/978-3-030-57552-6_16",

language = "English",

isbn = "978-3-030-57551-9",

booktitle = "Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings",

note = "International Congress on Health Sciences and Medical Technologies, ICHSMT 2019 ; Conference date: 05-12-2019 Through 07-12-2019",

}

Fernandes, SR, Assis, JTD, Estrela, VV, Razmjooy, N, Deshpande, A, Patavardhan, P, Aroma, RJ, Raimond, K, Loschi, HJ & Nascimento, DA 2021, Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors. in Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings: Proceedings of the ICHSMT 2019. International Congress on Health Sciences and Medical Technologies, ICHSMT 2019, Tlemcen, Algeria, 5/12/19. https://doi.org/10.1007/978-3-030-57552-6_16

Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors. / Fernandes, Sandro R.; Assis, Joaquim T. de; Estrela, Vania Vieira et al.
Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings: Proceedings of the ICHSMT 2019. 2021.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors

AU - Fernandes, Sandro R.

AU - Assis, Joaquim T. de

AU - Estrela, Vania Vieira

AU - Razmjooy, Navid

AU - Deshpande, Anand

AU - Patavardhan, P.

AU - Aroma, R. J.

AU - Raimond, K.

AU - Loschi, Hermes J.

AU - Nascimento, Douglas A.

PY - 2021

Y1 - 2021

N2 - X-ray computed microtomography (μCT or micro-CT) allows a nondestructive analysis of samples, which helps their reuse. The X-ray μCT equipment offers the user several configuration options that change the quality of the images obtained, thus affecting the expected result. In this study, a methodology for analyzing X-ray μCT images generated by the SkyScan 1174 Compact Micro-CT equipment was developed. The basis of this analysis methodology is texture descriptors. Three sets of images were used, and then degradations and noise were applied to the original images, generating new images. Subsequently, the following texture descriptors assisted in scrutinizing the sets: maximum probability, the moment of difference, the inverse difference moment, entropy, and uniformity. Experiments show the outcomes of some tests.

AB - X-ray computed microtomography (μCT or micro-CT) allows a nondestructive analysis of samples, which helps their reuse. The X-ray μCT equipment offers the user several configuration options that change the quality of the images obtained, thus affecting the expected result. In this study, a methodology for analyzing X-ray μCT images generated by the SkyScan 1174 Compact Micro-CT equipment was developed. The basis of this analysis methodology is texture descriptors. Three sets of images were used, and then degradations and noise were applied to the original images, generating new images. Subsequently, the following texture descriptors assisted in scrutinizing the sets: maximum probability, the moment of difference, the inverse difference moment, entropy, and uniformity. Experiments show the outcomes of some tests.

U2 - 10.1007/978-3-030-57552-6_16

DO - 10.1007/978-3-030-57552-6_16

M3 - Conference contribution

SN - 978-3-030-57551-9

BT - Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings

T2 - International Congress on Health Sciences and Medical Technologies, ICHSMT 2019

Y2 - 5 December 2019 through 7 December 2019

ER -

Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors

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