Mammogram mass classification based on discrete wavelet transform textural features

Abstract

This paper proposes an algorithm for early detection of breast cancer. This work incorporates Manual segmentation and textural analysis for the mammogram mass classification. Discrete Wavelet Transform (DWT) features act as a powerful input to the classifiers. A total of 148 mammogram images were taken from authentic mini MIAS database and under the… (More)
DOI: 10.1109/ICACCI.2014.6968479

Topics

Cite this paper

@article{Jaleel2014MammogramMC, title={Mammogram mass classification based on discrete wavelet transform textural features}, author={J. Abdul Jaleel and Sibi Salim and Archana. S}, journal={2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)}, year={2014}, pages={718-722} }