CLASSIFICATION OF BENIGN AND MALIGNANT BREAST TUMORS IN DIGITAL MAMMOGRAMS USING DIFFERENT WAVELET TRANSFORMS
Adapureddi Krishna Veni
, Ummadi Sathish Kumar
Breast Cancer, DWT, KNN, MIAS
Breast cancer is the leading cause of most deaths in the world. This paper deals with classification of Breast cancer, i.e. benign or malignant based on coefficients extracted from multiresolution analysis based on five different wavelet functions Biorthogonal 3.5, coifelts 3, Daubechies 4 and Symlets 3. In this paper 80 Region of Interest (ROI’s) from The Mammographic image analysis society(MIAS). The coefficients which extract the texture information from the ROI’s of Mammogram are given as an input to the KNN classifier. The performance of the system is evaluated using Receiver Operating Characteristic curve (ROC). Experimental results show that the area under the curve (AUC) is Az=0.90.
"CLASSIFICATION OF BENIGN AND MALIGNANT BREAST TUMORS IN DIGITAL MAMMOGRAMS USING DIFFERENT WAVELET TRANSFORMS", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 7, page no.293 - 296, July-2017, Available :https://ijsdr.org/papers/IJSDR1707048.pdf
Volume 2
Issue 7,
July-2017
Pages : 293 - 296
Paper Reg. ID: IJSDR_170660
Published Paper Id: IJSDR1707048
Downloads: 000347203
Research Area: Engineering
Country: vishakapatnam, Andhra pradesh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
