An Improved Decision Tree based Mammogram Image Classification of Breast Cancer for Decision Support Systems
N. Arivazhagan1, V. Govindharajan2
1N. Arivazhagan, Research Scholar, School of Computing, SRMIST, Chennai (Tamil Nadu), India.
2V. Govindharajan, Professor, School of Public Health Sciences, SRMIST, Chennai (Tamil Nadu), India.
Manuscript received on 14 December 2018 | Revised Manuscript received on 26 December 2018 | Manuscript Published on 24 January 2019 | PP: 129-131 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: Es2050017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Decision support system is used in medical field to enable the physician to make quick and efficient diagnosis of diseases using information and communication technology. Quick retrieval of image sample for comparison and classification is one of the important criteria for the design of such a system. Fast decision and accuracy of the classification is always trade off. The fast decision and retrieval usually suffer from a problem of less accuracy. Here in this paper a hybrid mechanism based image retrieval cum classification is proposed which will make quick decision with guaranteed level of accuracy. The proposed system is tested on mammogram medical images for finding early detection of cancer at various stages .The computational complexity analysis result on large image data base system proves the proposed scheme can be implementable in a typical practical decision support system.
Keywords: Mamogram Images, Decision Support Systems, Early Cancer Detection.
Scope of the Article: Classification