Abstract
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.
Translated title of the contribution | Segmentation of precursor lesions in cervical cancer using convolutional neural networks |
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Original language | Turkish |
Title of host publication | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781509064946 |
DOIs | |
Publication status | Published - 27 Jun 2017 |
Event | 25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey Duration: 15 May 2017 → 18 May 2017 |
Publication series
Name | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 |
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Conference
Conference | 25th Signal Processing and Communications Applications Conference, SIU 2017 |
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Country/Territory | Turkey |
City | Antalya |
Period | 15/05/17 → 18/05/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.