Identification and grouping of brain related tumors by applying hybrid LSF model

Abstract

This paper explores how technological advances can help in better diagnosis of cancer affected region of the brain. There has been exponential increase in brain tumor cases in recent pasts and there has been a gap in existing technology for root cause analysis. New reports indicate that various brain tumors can be treated through surgery and in exceptional cases with radiation. Image segmentation provides huge potential in diagnosis and treatment of brain tumors. Image segmentation helps to find volume and growth of tumor with usage of techniques such as human edge correction, outer edge coloring and inter active thresholds holdings. There is critical requirement to find out an automatic or semi automatic method for classification of brain tumor images, to eliminate human error and provide accurate results in MRI images. A new approach ‘LSF HYBRID model’ has been developed for detention and classification of brain cancer. System dependant actions such mechanisms leverage To locate the block and classify the brain tumor, this LSF HYBRID method users system dependant actions. It also utilizes other mechanisms such as Image enhancement, segmentation and Equalization of histogram.