Multi feature fusion using deep belief network for automatic pap-smear cell image classification

Moh Faturrahman, Ito Wasito, Ratna Mufidah, Fakhirah Dianah Ghaisani

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

Abstract

Early detection of cervical cancer plays an important rule to prevent the cancer metastasis. One of the common approach to early detection of cervical cancer is pap-smear image analysis. Nevertheless the manual pap- smear image analysis have some drawbacks such as provides inconsistent result, takes long time and prone to error occur. Therefore automatic pap-smear cell image classification is required to help pathologist choose the appropriate treatment to patients. In this study, authors propose multi feature fussion among Local Binary Pattern (LBP), Gray Level Co-Occurence Matrix (GLCM) and Shape Features using Deep Belief Network (DBN) for pap- smear cell image classification. The aim of this study is to measure the accuracy of two class classification of pap- smear cell image by the proposed method. The result shows that proposed method achieves the best accuracy at 97.35 % and slightly outperforms existing methods.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Computer, Control, Informatics and its Applications
Subtitle of host publicationEmerging Trends In Computational Science and Engineering, IC3INA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages18-22
Number of pages5
ISBN (Electronic)9781538639788
DOIs
Publication statusPublished - 8 Jan 2018
Event5th International Conference on Computer, Control, Informatics and its Applications, IC3INA 2017 - Jakarta, Indonesia
Duration: 23 Oct 201726 Oct 2017

Publication series

NameProceedings - 2017 International Conference on Computer, Control, Informatics and its Applications: Emerging Trends In Computational Science and Engineering, IC3INA 2017
Volume2018-January

Conference

Conference5th International Conference on Computer, Control, Informatics and its Applications, IC3INA 2017
CountryIndonesia
CityJakarta
Period23/10/1726/10/17

Keywords

  • Classification
  • Deep Belief Networks
  • GLCM
  • LBP
  • Multi-feature
  • Pap-Smear Image
  • fussion

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