DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded

News and Updates

Author can submit their paper through online submission. Click here

Paper Submission -> Blind Peer Review Process -> Acceptance -> Publication.

On an average time is 3 to 5 days from submission to first decision of manuscripts.

Double blind review and Plagiarism report ensure the originality

IJDMTA provides online manuscript tracking system.

Every issue of Journal of IJDMTA is available online from volume 1 issue 1 to the latest published issue with month and year.

Paper Submission:
Any Time
Review process:
One to Two week
Journal Publication:
June / December

IJDMTA special issue invites the papers from the NATIONAL CONFERENCE, INTERNATIONAL CONFERENCE, SEMINAR conducted by colleges, university, etc. The Group of paper will accept with some concession and will publish in IJDMTA website. For complete procedure, contact us at admin@iirgroups.org

Paper Template
Copyright Form
Subscription Form
web counter
web counter
Published in:   Vol. 4 Issue 2 Date of Publication:   December 2015

Prediction of Tumor in Classifying Mammogram images by k-Means, J48 and CART Algorithms

E.Venkatesan,T.Velmurugan

Page(s):   97-102 ISSN:   2278-2397
DOI:   10.20894/IJDMTA.102.004.002.011 Publisher:   Integrated Intelligent Research (IIR)

The Breast cancer is one of the leading cancers for women in world countries including India. It is the second most common causes of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last few years. Detecting cancer in the later stages, leads to very complicated surgeries and the chances of death is very high nowadays. Early detection of Breast Cancer helps in less complicated procedures and early recovery. Many tests have been found so as to detect cancer. Some of those tests are mammography, ultrasound etc. Mammography is a method that helps in early detection of Breast Cancer. But finding the mass and its spread from mammographic images is very difficult. Expert radiologists were needed for accurate reading of a mammogram image, and analyses have been for k- Means algorithm which helps for easy detection and extraction tumor area. The mammography image helps to provide some criteria in order to help the physicians to decide whether a certain disease is abnormal or normal. This research work is to identify the breast cancer tumor area and find its affected region by splitting the images into five clusters. The tumor area has been identified in the last cluster and classified with the help of decision tree algorithms J48 and CART.