Development of efficient image quarrying technique for Mammographic image classification to detect breast cancer with supervised learning algorithm

S. Julian Savari Antony, S. Ravi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This Breast cancer is one of the most prevalent lumps in women increased day by day around in worldwide. The scheme for the detection of breast cancer is Mammographic technique that is used at the very earlier stage. In this paper two kinds of classification Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) are used to analyze the mammographic images. The two classification methods are using the image pre-processing in wavelet decomposition and image enhancement. The results are verified with 322 mammogram images which is size for 1024×1024 with PGM format. The results show that the proposed algorithm can able to classify the images with a good performance rate of 98% It can be concluded that supervised learning algorithm gives fast and accurate classification and it works as efficient tool for classification of breast cancer cells.

Original languageEnglish
Title of host publicationICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems
Subtitle of host publicationBringing to the Table, Futuristic Technologies from Around the Globe
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479935062
DOIs
Publication statusPublished - Jan 1 2014
Event2013 International Conference on Advanced Computing and Communication Systems, ICACCS 2013 - Coimbatore, India
Duration: Dec 19 2013Dec 21 2013

Other

Other2013 International Conference on Advanced Computing and Communication Systems, ICACCS 2013
CountryIndia
CityCoimbatore
Period12/19/1312/21/13

Fingerprint

Quarrying
Image classification
Supervised learning
Learning algorithms
Wavelet decomposition
Image enhancement
Discriminant analysis
Support vector machines
Cells
Processing

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Antony, S. J. S., & Ravi, S. (2014). Development of efficient image quarrying technique for Mammographic image classification to detect breast cancer with supervised learning algorithm. In ICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems: Bringing to the Table, Futuristic Technologies from Around the Globe [6938688] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCS.2013.6938688
Antony, S. Julian Savari ; Ravi, S. / Development of efficient image quarrying technique for Mammographic image classification to detect breast cancer with supervised learning algorithm. ICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems: Bringing to the Table, Futuristic Technologies from Around the Globe. Institute of Electrical and Electronics Engineers Inc., 2014.
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Antony, SJS & Ravi, S 2014, Development of efficient image quarrying technique for Mammographic image classification to detect breast cancer with supervised learning algorithm. in ICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems: Bringing to the Table, Futuristic Technologies from Around the Globe., 6938688, Institute of Electrical and Electronics Engineers Inc., 2013 International Conference on Advanced Computing and Communication Systems, ICACCS 2013, Coimbatore, India, 12/19/13. https://doi.org/10.1109/ICACCS.2013.6938688

Development of efficient image quarrying technique for Mammographic image classification to detect breast cancer with supervised learning algorithm. / Antony, S. Julian Savari; Ravi, S.

ICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems: Bringing to the Table, Futuristic Technologies from Around the Globe. Institute of Electrical and Electronics Engineers Inc., 2014. 6938688.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Antony SJS, Ravi S. Development of efficient image quarrying technique for Mammographic image classification to detect breast cancer with supervised learning algorithm. In ICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems: Bringing to the Table, Futuristic Technologies from Around the Globe. Institute of Electrical and Electronics Engineers Inc. 2014. 6938688 https://doi.org/10.1109/ICACCS.2013.6938688