Review of Various Brain Tumor Detection Techniques with Machine Learning

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 . In the improvement more features like tissue color will be added which improve detection rate. The techniques which are already proposed are reviewed in this paper. The already proposed techniques are reviewed in terms of technique, advantages, disadvantages and outcomes.