To Detect and Classify the Breast Cancer Using Ultrasonography with Freak Detection Technique

Abstract

The breast cancer will be detected at early stage which is an important for efficient management of the disease in women.To recognize the breast cancer at in the early stage, we make use of a technique calledUltrasonography.The US used to produce the images of internal tissues.  This technique is painless and very safe which is the less expensive method.  In this paper we proposed to detect and classify the breast cancer using Ultrasonography with FREAK detection technique.The Ultrasonography image noise will be removed by the adaptive filters.   The US images are to be segmented with the help of the Pyramidal watershed segmentation and Fuzzy clustering techniques.  FREAK detection technique helps to detect the features from the after completion of the segmentation process.The features set will be extracted based on the method like machine learning features.  The recurrent neural network (RNN) classification technique is to be used for classification technique present in this paper.  RNN is the artificial neural network which is known as the connections between the nodes from the directed graph along sequence.  The simulation and result shows that there is the analysis of the performance with various parameters such as accuracy, true positive rate, false positive rate, true negative rate and false negative rate.