Developing a hybrid algorithm to detect brain tumors from MRI images

Abstract Background Image processing technologies have been developed in the past two decades to help clinicians diagnose tumors using medical images. Computer-aided diagnosis systems (CADs) have proven their ability to increase clinicians' detection rate of positive cases by 10% and have become integrated with many medical imaging systems and technologies. The study aimed to develop a hybrid algorithm to help doctors detect brain tumors from magnetic resonance imaging images. Results We were able to reach a detection accuracy of 96.6% and design a computer application that allows the user to enter the image and identify the location of the tumor in it if it exists with many additional features. Conclusions This approach can be improved by using different segmentation techniques, extracting additional features, or using other classifiers.