Brain Tumor Detection by Machine Leaning Approach Source Code & Document

Project Discription

As the tumor segmentation assumes critical part in brain tumor treatment. So proposed strategy use the best possible filtration way to deal with section the MRI picture of brain tumor into tumor and non tumor area. Medical diagnosis depend on testing equipment, pathology tests, and doctor experience. So this work has proposed FSGA a model for brain tumor detection in MRI images. Pre-processing of input image was done by weiner filter for removing noise. Input brain MRI image skull pixels were also identified and removed in the work to reduce the confusion in image segmentation. It is obtained that proposed fish schooling genetic algorithm which segments the image with high accuracy. This work has increased the accuracy of the segmentation so the medical diagnosis gets easy and fast. Here overall precision and recall values are also good from segmentation view.

Project Sample Image