Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma

Gökalp Tulum; Onur Osman; Özgür Dandin; Bülent Bolat; Tuncer Ergin; Ferhat Cüce

doi:10.1109/EBBT.2019.8741701

Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma

Translated title of the contribution: Colonic polyp classification using projection image and convolutional neural network

Gökalp Tulum, Onur Osman, Özgür Dandin, Bülent Bolat, Tuncer Ergin, Ferhat Cüce

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

1 Citation (Scopus)

Abstract

Nowadays, Computer-aided detection (CAD) systems are used to assist radiologists to detect colonic polyps. In this work, we aimed to develop convolutional neural network based classification system for automated detection of polyps. 2D projection images of polyps were used as the input of convolutional neural network. Our classification system performs at 91.89% sensitivity for polyps with 0 false positives per dataset.

Translated title of the contribution	Colonic polyp classification using projection image and convolutional neural network
Original language	Turkish
Title of host publication	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728110134
DOIs	https://doi.org/10.1109/EBBT.2019.8741701
Publication status	Published - Apr 2019
Externally published	Yes
Event	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 - Istanbul, Turkey Duration: 24 Apr 2019 → 26 Apr 2019

Publication series

Name	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019

Conference

Conference	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019
Country/Territory	Turkey
City	Istanbul
Period	24/04/19 → 26/04/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Access to Document

10.1109/EBBT.2019.8741701

Cite this

Tulum, G., Osman, O., Dandin, Ö., Bolat, B., Ergin, T., & Cüce, F. (2019). Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma. In 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 Article 8741701 (2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EBBT.2019.8741701

Tulum, Gökalp ; Osman, Onur ; Dandin, Özgür et al. / Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma. 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019).

@inproceedings{68d3cc26d58944568f24ca9a1f2bce06,

title = "Kolonik polip iz d{\"u}{\c s}{\"u}m g{\"o}r{\"u}nt{\"u}lerinde konvol{\"u}syonel sinir aǧi ile siniflandirma",

abstract = "Nowadays, Computer-aided detection (CAD) systems are used to assist radiologists to detect colonic polyps. In this work, we aimed to develop convolutional neural network based classification system for automated detection of polyps. 2D projection images of polyps were used as the input of convolutional neural network. Our classification system performs at 91.89% sensitivity for polyps with 0 false positives per dataset.",

keywords = "Convolutional neural network, Polyp classification",

author = "G{\"o}kalp Tulum and Onur Osman and {\"O}zg{\"u}r Dandin and B{\"u}lent Bolat and Tuncer Ergin and Ferhat C{\"u}ce",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 ; Conference date: 24-04-2019 Through 26-04-2019",

year = "2019",

month = apr,

doi = "10.1109/EBBT.2019.8741701",

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

series = "2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019",

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

booktitle = "2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019",

address = "United States",

}

Tulum, G, Osman, O, Dandin, Ö, Bolat, B, Ergin, T & Cüce, F 2019, Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma. in 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019., 8741701, 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019, Institute of Electrical and Electronics Engineers Inc., 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019, Istanbul, Turkey, 24/04/19. https://doi.org/10.1109/EBBT.2019.8741701

Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma. / Tulum, Gökalp; Osman, Onur; Dandin, Özgür et al.
2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8741701 (2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019).

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

TY - GEN

T1 - Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma

AU - Tulum, Gökalp

AU - Osman, Onur

AU - Dandin, Özgür

AU - Bolat, Bülent

AU - Ergin, Tuncer

AU - Cüce, Ferhat

PY - 2019/4

Y1 - 2019/4

N2 - Nowadays, Computer-aided detection (CAD) systems are used to assist radiologists to detect colonic polyps. In this work, we aimed to develop convolutional neural network based classification system for automated detection of polyps. 2D projection images of polyps were used as the input of convolutional neural network. Our classification system performs at 91.89% sensitivity for polyps with 0 false positives per dataset.

AB - Nowadays, Computer-aided detection (CAD) systems are used to assist radiologists to detect colonic polyps. In this work, we aimed to develop convolutional neural network based classification system for automated detection of polyps. 2D projection images of polyps were used as the input of convolutional neural network. Our classification system performs at 91.89% sensitivity for polyps with 0 false positives per dataset.

KW - Convolutional neural network

KW - Polyp classification

UR - http://www.scopus.com/inward/record.url?scp=85068563405&partnerID=8YFLogxK

U2 - 10.1109/EBBT.2019.8741701

DO - 10.1109/EBBT.2019.8741701

M3 - Konferans katkısı

AN - SCOPUS:85068563405

T3 - 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019

BT - 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019

Y2 - 24 April 2019 through 26 April 2019

ER -

Tulum G, Osman O, Dandin Ö, Bolat B, Ergin T, Cüce F. Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma. In 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8741701. (2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019). doi: 10.1109/EBBT.2019.8741701

Kolonik polip iz düşüm görüntülerinde konvolüsyonel sinir aǧi ile siniflandirma

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this