GA Based Neuro Fuzzy Techniques for Breast Cancer Identification

Abstract

An intelligent computer-aided diagnostics system may be developed to assist the radiologists to recognize the masses / lesions appearing in breast in different groups of benignancy / malignancy. In present work we have attempted to develop a computer assisted treatment planning system implementing Genetic algorithm based Neuro-fuzzy approaches. The boundary based features of the tumor lesions appearing in breast have been extracted for classification. The shape features represented by Fourier Descriptors, introduce a large number of feature vectors. Thus to classify different boundaries, a standard classifier needs a large number of inputs, and simultaneously to train the classifier a large number of training cycles are required. This may invite the problem of over learning, followed by chance of misclassification. In proposed methodology, Genetic Algorithm (GA) has been used for searching of significant input feature vectors. Finally adaptive neuro fuzzy based classifier has been introduced for classification of tumor masses in breast.

Pancreatic Cancer Prediction Through an Artificial Neural Network

“…The artificial neural network (ANN), which is based on the brain's neural structure (Rosenblatt, 1958 ), raised the interest of scientific community worldwide in the field of medicine due to its potential for diagnostic and prognostic applications (Smith et al, 1988 ; Salim, 2004 ; Kamruzzaman et al, 2010 ; Patil and Mudholkar, 2012 ). It has been used in heart disease (Kamruzzaman et al, 2010 ), predicting headache, pre-diagnosis of hypertension (Sumathi and Santhakumaran, 2011 ), kidney stone diseases (Kumar and Abhishek, 2012 ), classifying breast masses to identify breast cancer (Das and Bhattacharya, 2008 ; Pandey et al, 2012 ), dermatologist-level classification of skin diseases/cancer (Bakpo and Kabari, 2011 ; Esteva et al, 2017 ), prediction of skin cancer and blood cancer (Payandeh et al, 2009 ; Esteva et al, 2017 ; Roffman et al, 2018a ), and diagnosis of PC (Sanoob et al, 2016 ). As an example of the workflow in these applications, classification of skin cancer was performed via a single convolutional neural network, which was trained with a dataset of 129,450 clinical images (Esteva et al, 2017 ).…”

Artificial Neural Network for Diagnosis of Pancreatic Cancer

“…In 2004, a NN based model is proposed by Kamruzzaman et al for the diagnosis of heart diseases [10]. In 2008, a Genetic Algorithm (GA) based technique for classifying tumour mass in breast and to identify breast cancer has been introduced [11]. A new method for Predicting Blood Cancer and Disorder is then developed by Payandeh [12] et al later.…”