Detection of Breast Cancer on Mammograms using Neural Network Approach
Navdeep Kaur, Ajay Shiv Sharma · 2018 International Conference on Computing, Power and Communication Technologies (GUCON) · 2018
In the existing paper, weight-based algorithm is used to classify the normal and cancer cells and it is been analyzed that weight-based algorithm taken long time to classify the data. To classify the data in minimum amount of time HMM classifier is used for classification. The second issue with weight-based algorithm is of accuracy. As due to weight calculation accuracy of classification is less which can be improved with the use of Bayesian classifier in the feature selection part on three features are used which are mass, density and margin which can be extendable to more features like tissue color which further improve the detection rate. The simulation is performed in MATLAB and it is been analyzed that proposed technique performs well in terms of fault detection rate, accuracy, MSE and PSNR.