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Brain's tumor image processing using shearlet transform. / Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin et al.

Applications of Digital Image Processing XL. ed. / AG Tescher. Vol. 10396 SPIE, 2017. 103961B (Proceedings of SPIE; Vol. 10396).

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

Harvard

Cadena, L, Espinosa, N, Cadena, F, Korneeva, A, Kruglyakov, A, Legalov, A, Romanenko, A & Zotin, A 2017, Brain's tumor image processing using shearlet transform. in AG Tescher (ed.), Applications of Digital Image Processing XL. vol. 10396, 103961B, Proceedings of SPIE, vol. 10396, SPIE, Applications of Digital Image Processing XL 2017, San Diego, United States, 07.08.2017. https://doi.org/10.1117/12.2272792

APA

Cadena, L., Espinosa, N., Cadena, F., Korneeva, A., Kruglyakov, A., Legalov, A., Romanenko, A., & Zotin, A. (2017). Brain's tumor image processing using shearlet transform. In AG. Tescher (Ed.), Applications of Digital Image Processing XL (Vol. 10396). [103961B] (Proceedings of SPIE; Vol. 10396). SPIE. https://doi.org/10.1117/12.2272792

Vancouver

Cadena L, Espinosa N, Cadena F, Korneeva A, Kruglyakov A, Legalov A et al. Brain's tumor image processing using shearlet transform. In Tescher AG, editor, Applications of Digital Image Processing XL. Vol. 10396. SPIE. 2017. 103961B. (Proceedings of SPIE). doi: 10.1117/12.2272792

Author

Cadena, Luis ; Espinosa, Nikolai ; Cadena, Franklin et al. / Brain's tumor image processing using shearlet transform. Applications of Digital Image Processing XL. editor / AG Tescher. Vol. 10396 SPIE, 2017. (Proceedings of SPIE).

BibTeX

@inproceedings{2a6239c77292410a8d7693802accd8b1,
title = "Brain's tumor image processing using shearlet transform",
abstract = "Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.",
keywords = "brain tumor detection, edge detection, image analysis, Medical imaging, shearlet transform",
author = "Luis Cadena and Nikolai Espinosa and Franklin Cadena and Anna Korneeva and Alexey Kruglyakov and Alexander Legalov and Alexey Romanenko and Alexander Zotin",
year = "2017",
doi = "10.1117/12.2272792",
language = "English",
isbn = "978-1-5106-1249-5",
volume = "10396",
series = "Proceedings of SPIE",
publisher = "SPIE",
editor = "AG Tescher",
booktitle = "Applications of Digital Image Processing XL",
address = "United States",
note = "Applications of Digital Image Processing XL 2017 ; Conference date: 07-08-2017 Through 10-08-2017",

}

RIS

TY - GEN

T1 - Brain's tumor image processing using shearlet transform

AU - Cadena, Luis

AU - Espinosa, Nikolai

AU - Cadena, Franklin

AU - Korneeva, Anna

AU - Kruglyakov, Alexey

AU - Legalov, Alexander

AU - Romanenko, Alexey

AU - Zotin, Alexander

PY - 2017

Y1 - 2017

N2 - Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

AB - Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

KW - brain tumor detection

KW - edge detection

KW - image analysis

KW - Medical imaging

KW - shearlet transform

UR - http://www.scopus.com/inward/record.url?scp=85034788773&partnerID=8YFLogxK

U2 - 10.1117/12.2272792

DO - 10.1117/12.2272792

M3 - Conference contribution

AN - SCOPUS:85034788773

SN - 978-1-5106-1249-5

VL - 10396

T3 - Proceedings of SPIE

BT - Applications of Digital Image Processing XL

A2 - Tescher, AG

PB - SPIE

T2 - Applications of Digital Image Processing XL 2017

Y2 - 7 August 2017 through 10 August 2017

ER -

ID: 9029934