Title :
Classifying Digital Mammogram Masses Using Univariate ANOVA Discriminant Analysis
Author :
Surendiran, B. ; Sundaraiah, Y. ; Vadivel, A.
Author_Institution :
Dept. of Comput. Applic., Nat. Inst. of Technol., Tiruchirappalli, India
Abstract :
An Univariate Analysis Of Variance (ANOVA) Discriminant Analysis (DA) classifier is proposed for classifying the masses present in mammogram. This approach combines the 19 shape properties of the mass regions and classifies the masses as benign or malignant using Univariate ANOVA. The experiment is performed on DDSM database images. Experimental results shows that the proposed method reaches high classification accuracy in compared to existing algorithms.
Keywords :
mammography; medical diagnostic computing; pattern classification; statistical analysis; digital mammogram; discriminant analysis classifier; univariate ANOVA discriminant analysis; univariate analysis of variance; Analysis of variance; Benign tumors; Breast cancer; Cancer detection; Delta-sigma modulation; Feature extraction; Histograms; Mammography; Neural networks; Shape; Classifying as Benign or Malignant; Digital Mammogram; Discriminant analysis; Shape properties; Univariate ANOVA;
Conference_Titel :
Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
Conference_Location :
Kottayam, Kerala
Print_ISBN :
978-1-4244-5104-3
Electronic_ISBN :
978-0-7695-3845-7
DOI :
10.1109/ARTCom.2009.33
