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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
  • Istanbul Technical University
  • Istanbul Medipol University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 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 contributionA deep learning based approach for classification of CerbB2 tumor cells in breast cancer
Original languageTurkish
Title of host publication2017 25th Signal Processing and Communications Applications Conference, SIU 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509064946
DOIs
Publication statusPublished - 27 Jun 2017
Event25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Duration: 15 May 201718 May 2017

Publication series

Name2017 25th Signal Processing and Communications Applications Conference, SIU 2017

Conference

Conference25th Signal Processing and Communications Applications Conference, SIU 2017
Country/TerritoryTurkey
CityAntalya
Period15/05/1718/05/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

UN SDGs

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

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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