Rahim Aǧzi (Serviks) Kanserinde Öncü Lezyonlarin Evrişimsel Sinir Aǧlariyla Bölütlenmesi

Abdulkadir Albayrak*, Asli Unlu, Nurullah Calik, Gokhan Bilgin, Ilknur Turkmen, Asli Cakir, Abdulkerim Capar, Behcet Ugur Toreyin, Lutfiye Durak Ata

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

13 Atıf (Scopus)

Özet

Cervical carcinoma is one of the frequently seen cancers in the world and in our country, develops from precursor lesions. These precursor lesions are analyzed by pathologists so that the diagnosis of the disease can be made. In this study, a system that performs automatic detection of pre-cancerous lesions was performed using the convolutional neural networks (CNNs). In the training phase, lesion recognition performance of the proposed system has reached 92%. Thereafter, whole image was segmented by using 60 × 60 pixel tiles during the training phase. After all, the precursor lesions were segmented with 81.71% Dice coefficient.

Tercüme edilen katkı başlığıSegmentation of precursor lesions in cervical cancer using convolutional neural networks
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2017 25th Signal Processing and Communications Applications Conference, SIU 2017
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781509064946
DOI'lar
Yayın durumuYayınlandı - 27 Haz 2017
Etkinlik25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Süre: 15 May 201718 May 2017

Yayın serisi

Adı2017 25th Signal Processing and Communications Applications Conference, SIU 2017

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???event.eventtypes.event.conference???25th Signal Processing and Communications Applications Conference, SIU 2017
Ülke/BölgeTurkey
ŞehirAntalya
Periyot15/05/1718/05/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Keywords

  • Cervical cancer
  • convolutional neural networks
  • histopathological images
  • precursor lesions
  • segmentation

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