Universiti Teknologi Malaysia Institutional Repository

Malignancy and abnormality detection of mammograms using discrete wavelet transformed features and neural network

Talha, Muhammad and Sulong, Ghazali and Naveed, Nawazish and Jaffar, Arfan (2012) Malignancy and abnormality detection of mammograms using discrete wavelet transformed features and neural network. Information, 15 (2). pp. 707-719. ISSN 1343-4500

Full text not available from this repository.

Abstract

Mammograms can be used to check for breast cancer in women. In this paper, we have proposed breast cancer detection into two stages. In the first stage, mammograms have to classify into malignant and benign. While in second stage, the type of abnormality is detected. Features have been extracted using Discrete Wavelet Transform. These wavelet based features has been reduced using Principle Component Analysis. Those images which have been classified as malignant in the first stage are further classified into six classes to check its abnormality. It has been observed that the accuracy of classification of abnormalities is more than 90%. Mammographic Institute Society Analysis dataset is used for experimentation.

Item Type:Article
Uncontrolled Keywords:Mammographic Institute Society Analysis, malignant, breast cancer
Subjects:Z Bibliography. Library Science. Information Resources > ZA Information resources
Divisions:Computer Science and Information System (Formerly known)
ID Code:47169
Deposited By: Narimah Nawil
Deposited On:22 Jun 2015 13:56
Last Modified:31 Mar 2019 16:34

Repository Staff Only: item control page