Performance Analysis Of Brain Tumor Detection Using Deep Learning And Machine Learning Models

Abstract

      Now A Days For Identifying Or Predict Any Diseases On Human Beings, We Should Have Proper Diagnosis For Predicting The Disease Which Is Present In That Human Body. In General For Prediction Of Diseases We Try To Use Either Ct Or Mri Scan Techniques For Taking Decision On That Appropriate Disease. In General Medical Person Need Complete Knowledge On That Appropriate Domain To Find Out The Abnormality Which Is Present In Human Beings. In This Present Article We Try To Discuss About The Brain Tumor Detection By Using Deep Learning And Machine Learning Models And Try To Find Out Which Mri Image Is Having Benign And Which Images Are Having Malignant . In Recent Days There Was Tremendous Success Of Ml Algorithms At Image Recognition Tasks And This Is Increasing Day By Day Because Of Electronic Medical Records And Diagnostic Imaging. If We Use Basic Ml Algorithms To Predict The Abnormality, This May Take Lot Of Time Complexity And Accuracy May Be Very Less. Hence In Our Current Application We Try To Develop The Model Using Cnn Deep Learning Architecture And Try To Show That Proposed Cnn Model Has High Efficiency And Accuracy Compared With Previous Ml Models. In This Current Article We Try To Discuss About The Key Research Areas And Applications Of Medical Image Classification, Localization, Detection, Segmentation. We Conclude By Discussing Research Obstacles, Emerging Trends, And Possible Future Directions For Improving Some More Advancement.