It is a medical challenge how to quickly and accurately diagnose brain tumor. In many cases the lesions of benign and malignant are difficult to differentiate. Physical examination and history of affected individual is recorded. CT, MRI and angiography are variety of brain imaging techniques. So far there are many imaging algorithms approaches that are used for brain lesion recognition but effective recognition is always remains a challenge. In this paper fuzzy minmax image processing algorithm is proposed. Image processing is usually a four step process mainly includes preprocessing, segmentation, feature extraction, accuracy detection. These stages are used to detect exact location of brain tumor. Study revealed that age, blood supply, Oedema, post contrast enhancement, signal intensity of T-1 weighted image etc. were the important investigation parameters. There were more than 20 fields which can be taken into consideration while performing image algorithm. Experiment result has been evaluated based on accuracy, specificity, sensitivity & dice similarity index. As studied the propose method will achieve accuracy of about 85% by considering six-seven features. Current approach is a review on advantages and disadvantages of medical imaging applications.