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

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

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

2 Atıf (Scopus)

Özet

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.

Tercüme edilen katkı başlığı	Colonic polyp classification using projection image and convolutional neural network
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781728110134
DOI'lar	https://doi.org/10.1109/EBBT.2019.8741701
Yayın durumu	Yayınlandı - Nis 2019
Harici olarak yayınlandı	Evet
Etkinlik	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 - Istanbul, Turkey Süre: 24 Nis 2019 → 26 Nis 2019

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019
Ülke/Bölge	Turkey
Şehir	Istanbul
Periyot	24/04/19 → 26/04/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

Keywords

Convolutional neural network
Polyp classification

Belgeye Erişim

10.1109/EBBT.2019.8741701

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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 Makale 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).

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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",

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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).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

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 - https://www.scopus.com/pages/publications/85068563405

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

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap