Neural Networks Oblige Diagnosis of the Ischemic CVA’s by MRI
Pallavi Srivastava *
Sanskriti University, Mathura, Uttar Pradesh, India.
Kirti Mishra
Sanskriti University, Mathura, Uttar Pradesh, India.
Chitrangada Chaubey
Sanskriti University, Mathura, Uttar Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
In present time the technological & computing evolution are promoted for new opportunities that will help to improve the standard of life between the new medical accomplishments, in particular and the standard of diagnostic evaluations. MRI is one of the imaging equipment for the diagnosis which has become more beneficial for technological development, because of this and due to the standard of a diagnosis manufacturer, that is one of the most engaging apparatus in the clinical application. The attentiveness in that pathology & in the general the encephalon picture analysis as the preventive diagnosis. The present research paper suggests the evaluation of the ability of ANN for the automatic identification of an ICVA by tissue images density obtained by MRI. In this examination the diagnosis and their medical reports were used to train the ANN classifier which extracted features from the given images. In this stage the ANN significantly contributes to the ICVA of MRI diagnosis aid, so since the test occurrence automatic identification of ischemic lesions that has been performed with the accuracy results that will be false positive and false negative.
Keywords: Artificial neural networks (ANN), diagnosis, identification, ischemic cerebral vascular accident (ICVA), magnetic resonance imaging (MRI)