Adversarial Nuclei Segmentation on HE Stained Histopathology Images

Onur Can Koyun; Tulay Yildirim

doi:10.1109/INISTA.2019.8778369

Adversarial Nuclei Segmentation on HE Stained Histopathology Images

Onur Can Koyun
, Tulay Yildirim

Yildiz Technical University

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

8 Atıf (Scopus)

Özet

Computer aided methods in pathology are advancing rapidly. Problems like segmentation, classification and detection of pathology images are solved with machine learning and image processing techniques. State-of-the-art methods in nuclei segmentation problem include supervised deep learning techniques. However, labeling process of pathology images is an expensive and time consuming process. In this work, nuclei segmentation problem is formulated as image-to-image translation problem and using Cycle-Consistent Generative Adversarial Networks, an unsupervised segmentation scheme is proposed for hematoxylineosin stained histopathology data.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings
Editörler	Petia Koprinkova-Hristova, Tuly Yildirim, Vincenzo Piuri, Lazaros Iliadis, David Camacho
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781728118628
DOI'lar	https://doi.org/10.1109/INISTA.2019.8778369
Yayın durumu	Yayınlandı - Tem 2019
Harici olarak yayınlandı	Evet
Etkinlik	2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Sofia, Bulgaria Süre: 3 Tem 2019 → 5 Tem 2019

Yayın serisi

Adı	IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings

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

???event.eventtypes.event.conference???	2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019
Ülke/Bölge	Bulgaria
Şehir	Sofia
Periyot	3/07/19 → 5/07/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

Belgeye Erişim

10.1109/INISTA.2019.8778369

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Koyun, O. C., & Yildirim, T. (2019). Adversarial Nuclei Segmentation on HE Stained Histopathology Images. In P. Koprinkova-Hristova, T. Yildirim, V. Piuri, L. Iliadis, & D. Camacho (Eds.), IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings Makale 8778369 (IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INISTA.2019.8778369

Koyun, Onur Can ; Yildirim, Tulay. / Adversarial Nuclei Segmentation on HE Stained Histopathology Images. IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings. editör / Petia Koprinkova-Hristova ; Tuly Yildirim ; Vincenzo Piuri ; Lazaros Iliadis ; David Camacho. Institute of Electrical and Electronics Engineers Inc., 2019. (IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings).

@inproceedings{6bfa6d3b40c441c49342f317c9d71515,

title = "Adversarial Nuclei Segmentation on HE Stained Histopathology Images",

abstract = "Computer aided methods in pathology are advancing rapidly. Problems like segmentation, classification and detection of pathology images are solved with machine learning and image processing techniques. State-of-the-art methods in nuclei segmentation problem include supervised deep learning techniques. However, labeling process of pathology images is an expensive and time consuming process. In this work, nuclei segmentation problem is formulated as image-to-image translation problem and using Cycle-Consistent Generative Adversarial Networks, an unsupervised segmentation scheme is proposed for hematoxylineosin stained histopathology data.",

keywords = "Adversary, Cell, Cycle, GAN, Nuclei, Segmentation, Unsupervised, pathology",

author = "Koyun, \{Onur Can\} and Tulay Yildirim",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 ; Conference date: 03-07-2019 Through 05-07-2019",

year = "2019",

month = jul,

doi = "10.1109/INISTA.2019.8778369",

language = "English",

series = "IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings",

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

editor = "Petia Koprinkova-Hristova and Tuly Yildirim and Vincenzo Piuri and Lazaros Iliadis and David Camacho",

booktitle = "IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings",

address = "United States",

}

Koyun, OC & Yildirim, T 2019, Adversarial Nuclei Segmentation on HE Stained Histopathology Images. in P Koprinkova-Hristova, T Yildirim, V Piuri, L Iliadis & D Camacho (eds), IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings., 8778369, IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019, Sofia, Bulgaria, 3/07/19. https://doi.org/10.1109/INISTA.2019.8778369

Adversarial Nuclei Segmentation on HE Stained Histopathology Images. / Koyun, Onur Can; Yildirim, Tulay.
IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings. ed. / Petia Koprinkova-Hristova; Tuly Yildirim; Vincenzo Piuri; Lazaros Iliadis; David Camacho. Institute of Electrical and Electronics Engineers Inc., 2019. 8778369 (IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings).

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

TY - GEN

T1 - Adversarial Nuclei Segmentation on HE Stained Histopathology Images

AU - Koyun, Onur Can

AU - Yildirim, Tulay

PY - 2019/7

Y1 - 2019/7

N2 - Computer aided methods in pathology are advancing rapidly. Problems like segmentation, classification and detection of pathology images are solved with machine learning and image processing techniques. State-of-the-art methods in nuclei segmentation problem include supervised deep learning techniques. However, labeling process of pathology images is an expensive and time consuming process. In this work, nuclei segmentation problem is formulated as image-to-image translation problem and using Cycle-Consistent Generative Adversarial Networks, an unsupervised segmentation scheme is proposed for hematoxylineosin stained histopathology data.

AB - Computer aided methods in pathology are advancing rapidly. Problems like segmentation, classification and detection of pathology images are solved with machine learning and image processing techniques. State-of-the-art methods in nuclei segmentation problem include supervised deep learning techniques. However, labeling process of pathology images is an expensive and time consuming process. In this work, nuclei segmentation problem is formulated as image-to-image translation problem and using Cycle-Consistent Generative Adversarial Networks, an unsupervised segmentation scheme is proposed for hematoxylineosin stained histopathology data.

KW - Adversary

KW - Cell

KW - Cycle

KW - GAN

KW - Nuclei

KW - Segmentation

KW - Unsupervised

KW - pathology

UR - https://www.scopus.com/pages/publications/85070749957

U2 - 10.1109/INISTA.2019.8778369

DO - 10.1109/INISTA.2019.8778369

M3 - Conference contribution

AN - SCOPUS:85070749957

T3 - IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings

BT - IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings

A2 - Koprinkova-Hristova, Petia

A2 - Yildirim, Tuly

A2 - Piuri, Vincenzo

A2 - Iliadis, Lazaros

A2 - Camacho, David

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019

Y2 - 3 July 2019 through 5 July 2019

ER -

Koyun OC, Yildirim T. Adversarial Nuclei Segmentation on HE Stained Histopathology Images. In Koprinkova-Hristova P, Yildirim T, Piuri V, Iliadis L, Camacho D, editörler, IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8778369. (IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2019 - Proceedings). doi: 10.1109/INISTA.2019.8778369

Adversarial Nuclei Segmentation on HE Stained Histopathology Images

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