MRI brain tumor detection based on soft computing

Medical image processing techniques are essential in detecting diseases at present. Usually, MRI images detect the presence and type of disease. The brain comprises a group nerve cells supportive tissues. Brain tumors one most dangerous types because high mortality rates they cause worldwide. detection tumor may be fundamental reason to save patient's life. rate was very before early diagnosis began. After starting diagnosis, death noticeably reduced due accurate identification stages. Currently, researchers have stepped up their efforts by using computer programs help clinicians classification tumors. In this research, an algorithm presented overcome problems diagnosing tumors, consisting several stages: first stage is get real data then make improvements Wiener filter. Then determined threshold, divided into more than section. Thus, entered on morphological process enhance segmentation result remove distortion filter out smaller regions. next step watershed used separate different region according intensity value which leads diagnoses tumor. Finally feature extraction obtain important information about optimal