Abnormal tissue detection in computer tomography images using artificial neural networks

Tamer Olmez; Ertugrul Yazgan

doi:10.1109/IEMBS.1992.5761344

Abnormal tissue detection in computer tomography images using artificial neural networks

Tamer Olmez, Ertugrul Yazgan

Department of Electronics and Communication Engineering

Istanbul Technical University

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

6 Citations (Scopus)

Abstract

Artificial neural network solutions have been applied to numerous image applications in the recent past. This paper describes a method to detect abnormal tissues in computer tomography (CT) head images by using an artificial neural network. We use a three-layer perceptron: An input layer with 882 nodes, one hidden layer with 30 nodes and an output layer with 3 nodes. The output nodes represent the bone, soft and abnormal tissue. The input layer of network does not directly receive the data from the original image. Two processes are applied to the pixels in subimage which has 7×7 pixels, and the results are fed to the input layer of the network. These processes provide necessary information for the tissue identification.

Original language	English
Title of host publication	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992
Editors	Jean Louis Coatrieux, Robert Plonsey, Swamy Laxminarayan, Jean Pierre Morucci
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	998-999
Number of pages	2
ISBN (Electronic)	0780307852
DOIs	https://doi.org/10.1109/IEMBS.1992.5761344
Publication status	Published - 1992
Event	14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992 - Paris, France Duration: 29 Oct 1992 → 1 Nov 1992

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	3
ISSN (Print)	1557-170X

Conference

Conference	14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992
Country/Territory	France
City	Paris
Period	29/10/92 → 1/11/92

Bibliographical note

Publisher Copyright:
© 1992 IEEE.

Access to Document

10.1109/IEMBS.1992.5761344

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Olmez, T., & Yazgan, E. (1992). Abnormal tissue detection in computer tomography images using artificial neural networks. In J. L. Coatrieux, R. Plonsey, S. Laxminarayan, & J. P. Morucci (Eds.), Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992 (pp. 998-999). Article 5761344 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMBS.1992.5761344

Olmez, Tamer ; Yazgan, Ertugrul. / Abnormal tissue detection in computer tomography images using artificial neural networks. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992. editor / Jean Louis Coatrieux ; Robert Plonsey ; Swamy Laxminarayan ; Jean Pierre Morucci. Institute of Electrical and Electronics Engineers Inc., 1992. pp. 998-999 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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title = "Abnormal tissue detection in computer tomography images using artificial neural networks",

abstract = "Artificial neural network solutions have been applied to numerous image applications in the recent past. This paper describes a method to detect abnormal tissues in computer tomography (CT) head images by using an artificial neural network. We use a three-layer perceptron: An input layer with 882 nodes, one hidden layer with 30 nodes and an output layer with 3 nodes. The output nodes represent the bone, soft and abnormal tissue. The input layer of network does not directly receive the data from the original image. Two processes are applied to the pixels in subimage which has 7×7 pixels, and the results are fed to the input layer of the network. These processes provide necessary information for the tissue identification.",

author = "Tamer Olmez and Ertugrul Yazgan",

note = "Publisher Copyright: {\textcopyright} 1992 IEEE.; 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992 ; Conference date: 29-10-1992 Through 01-11-1992",

year = "1992",

doi = "10.1109/IEMBS.1992.5761344",

language = "English",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

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Olmez, T & Yazgan, E 1992, Abnormal tissue detection in computer tomography images using artificial neural networks. in JL Coatrieux, R Plonsey, S Laxminarayan & JP Morucci (eds), Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992., 5761344, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 3, Institute of Electrical and Electronics Engineers Inc., pp. 998-999, 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992, Paris, France, 29/10/92. https://doi.org/10.1109/IEMBS.1992.5761344

Abnormal tissue detection in computer tomography images using artificial neural networks. / Olmez, Tamer; Yazgan, Ertugrul.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992. ed. / Jean Louis Coatrieux; Robert Plonsey; Swamy Laxminarayan; Jean Pierre Morucci. Institute of Electrical and Electronics Engineers Inc., 1992. p. 998-999 5761344 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 3).

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

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AB - Artificial neural network solutions have been applied to numerous image applications in the recent past. This paper describes a method to detect abnormal tissues in computer tomography (CT) head images by using an artificial neural network. We use a three-layer perceptron: An input layer with 882 nodes, one hidden layer with 30 nodes and an output layer with 3 nodes. The output nodes represent the bone, soft and abnormal tissue. The input layer of network does not directly receive the data from the original image. Two processes are applied to the pixels in subimage which has 7×7 pixels, and the results are fed to the input layer of the network. These processes provide necessary information for the tissue identification.

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BT - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992

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Olmez T, Yazgan E. Abnormal tissue detection in computer tomography images using artificial neural networks. In Coatrieux JL, Plonsey R, Laxminarayan S, Morucci JP, editors, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 1992. Institute of Electrical and Electronics Engineers Inc. 1992. p. 998-999. 5761344. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/IEMBS.1992.5761344

Abnormal tissue detection in computer tomography images using artificial neural networks

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