Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim

Gozde A. Tataroglu; Anil Genc; Kaan A. Kabakci; Abdulkerim Capar; B. Ugur Toreyin; Hazim K. Ekenel; Ilknur Turkmen; Asli Cakir

doi:10.1109/SIU.2017.7960587

Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim

Translated title of the contribution: A deep learning based approach for classification of CerbB2 tumor cells in breast cancer

Gozde A. Tataroglu^*, Anil Genc, Kaan A. Kabakci, Abdulkerim Capar, B. Ugur Toreyin, Hazim K. Ekenel, Ilknur Turkmen, Asli Cakir

^*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the cell fragments were classified with high performance by the aid of convolutional neural networks (CNN).

Translated title of the contribution	A deep learning based approach for classification of CerbB2 tumor cells in breast cancer
Original language	Turkish
Title of host publication	2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509064946
DOIs	https://doi.org/10.1109/SIU.2017.7960587
Publication status	Published - 27 Jun 2017
Event	25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey Duration: 15 May 2017 → 18 May 2017

Publication series

Name	2017 25th Signal Processing and Communications Applications Conference, SIU 2017

Conference

Conference	25th Signal Processing and Communications Applications Conference, SIU 2017
Country/Territory	Turkey
City	Antalya
Period	15/05/17 → 18/05/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/SIU.2017.7960587

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Tataroglu, G. A., Genc, A., Kabakci, K. A., Capar, A., Toreyin, B. U., Ekenel, H. K., Turkmen, I., & Cakir, A. (2017). Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim. In 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 Article 7960587 (2017 25th Signal Processing and Communications Applications Conference, SIU 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2017.7960587

Tataroglu, Gozde A. ; Genc, Anil ; Kabakci, Kaan A. et al. / Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim. 2017 25th Signal Processing and Communications Applications Conference, SIU 2017. Institute of Electrical and Electronics Engineers Inc., 2017. (2017 25th Signal Processing and Communications Applications Conference, SIU 2017).

@inproceedings{f9d4ba87d20d4c53acc7012b931a01a0,

title = "Meme Kanserinde CerbB2 T{\"u}m{\"o}r H{\"u}crelerinin Siniflandirilmasi i{\c c}in Derin {\"O}ǧrenme Tabanli Bir Yakla{\c s}im",

abstract = "This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the cell fragments were classified with high performance by the aid of convolutional neural networks (CNN).",

keywords = "CerbB2 marker, Convolutional Neural Networks (CNN), classification, score, tumor",

author = "Tataroglu, {Gozde A.} and Anil Genc and Kabakci, {Kaan A.} and Abdulkerim Capar and Toreyin, {B. Ugur} and Ekenel, {Hazim K.} and Ilknur Turkmen and Asli Cakir",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 25th Signal Processing and Communications Applications Conference, SIU 2017 ; Conference date: 15-05-2017 Through 18-05-2017",

year = "2017",

month = jun,

day = "27",

doi = "10.1109/SIU.2017.7960587",

language = "T{\"u}rk{\c c}e",

series = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",

address = "United States",

}

Tataroglu, GA, Genc, A, Kabakci, KA, Capar, A , Toreyin, BU , Ekenel, HK, Turkmen, I & Cakir, A 2017, Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim. in 2017 25th Signal Processing and Communications Applications Conference, SIU 2017., 7960587, 2017 25th Signal Processing and Communications Applications Conference, SIU 2017, Institute of Electrical and Electronics Engineers Inc., 25th Signal Processing and Communications Applications Conference, SIU 2017, Antalya, Turkey, 15/05/17. https://doi.org/10.1109/SIU.2017.7960587

Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim. / Tataroglu, Gozde A.; Genc, Anil; Kabakci, Kaan A. et al.
2017 25th Signal Processing and Communications Applications Conference, SIU 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7960587 (2017 25th Signal Processing and Communications Applications Conference, SIU 2017).

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

TY - GEN

T1 - Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim

AU - Tataroglu, Gozde A.

AU - Genc, Anil

AU - Kabakci, Kaan A.

AU - Capar, Abdulkerim

AU - Toreyin, B. Ugur

AU - Ekenel, Hazim K.

AU - Turkmen, Ilknur

AU - Cakir, Asli

PY - 2017/6/27

Y1 - 2017/6/27

N2 - This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the cell fragments were classified with high performance by the aid of convolutional neural networks (CNN).

AB - This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the cell fragments were classified with high performance by the aid of convolutional neural networks (CNN).

KW - CerbB2 marker

KW - Convolutional Neural Networks (CNN)

KW - classification

KW - score

KW - tumor

UR - http://www.scopus.com/inward/record.url?scp=85026309134&partnerID=8YFLogxK

U2 - 10.1109/SIU.2017.7960587

DO - 10.1109/SIU.2017.7960587

M3 - Konferans katkısı

AN - SCOPUS:85026309134

T3 - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

BT - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th Signal Processing and Communications Applications Conference, SIU 2017

Y2 - 15 May 2017 through 18 May 2017

ER -

Tataroglu GA, Genc A, Kabakci KA, Capar A , Toreyin BU , Ekenel HK et al. Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim. In 2017 25th Signal Processing and Communications Applications Conference, SIU 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 7960587. (2017 25th Signal Processing and Communications Applications Conference, SIU 2017). doi: 10.1109/SIU.2017.7960587

Meme Kanserinde CerbB2 Tümör Hücrelerinin Siniflandirilmasi için Derin Öǧrenme Tabanli Bir Yaklaşim

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

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