Local linear wavelet neural network for breast cancer recognition

2011 ◽  
Vol 22 (1) ◽  
pp. 125-131 ◽  
Author(s):  
M. R. Senapati ◽  
A. K. Mohanty ◽  
S. Dash ◽  
P. K. Dash
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Wavelet Neural Network ◽  
Local Linear

A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

2009 ◽  
Vol 129 (7) ◽  
pp. 1356-1362
Author(s):  
Kunikazu Kobayashi ◽  
Masanao Obayashi ◽  
Takashi Kuremoto
Keyword(s):  
Neural Network ◽  
Design Method ◽  
Wavelet Neural Network ◽  
Bayesian Design ◽  
Local Linear

Time-series prediction using a local linear wavelet neural network

2006 ◽  
Vol 69 (4-6) ◽  
pp. 449-465 ◽  
Author(s):  
Yuehui Chen ◽  
Bo Yang ◽  
Jiwen Dong
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Series Prediction ◽  
Wavelet Neural Network ◽  
Local Linear

An Intelligent-Based Wavelet Classifier for Accurate Prediction of Breast Cancer

2018 ◽  
pp. 306-319 ◽  
Author(s):  
Anandakumar Haldorai ◽  
Arulmurugan Ramu
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Roc Curve ◽  
Breast Tissue ◽  
Wavelet Neural Network ◽  
Clinical Database ◽  
New Approach ◽  
X Ray ◽  
Breast Tissues

The detection of cancer in the breast is done using mammograms (x-ray images). The authors propose a CAD framework for distinguishing little changes in mammogram which may demonstrate malignancies which are too little to be felt either by the lady herself or by a radiologist. In this chapter, they build up a framework for analysis, visualization, and prediction of cancer in breast tissue by utilizing Intelligent based wavelet classifier. Intelligent-based wavelet classifier is a new approach constructed using texture value and wavelet neural network. The proposed framework is applied to the genuine clinical database of 160 mammograms gathered from mammogram screening focuses. The execution of the CAD framework is examined utilizing ROC curve. This will help the specialists in determination of the breast tissues either cancerous or noncancerous in an accurate way.

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