Abstract

Abstract:- This work deals with the implementation of the Basic Tumor Range and Shape Detection Algorithm in brain MR images and identifies the tumor stage from the tumor region. In every part of the body, a tumor is an uncontrolled growth of tissues. There are various types of tumors and they have different characteristics and different therapies. As is understood, because of its presence in the small space of the intracranial cavity, the brain tumor is inherently extreme and life-threatening (space formed inside the skull). Most studies in developing countries indicates that due to inaccurate diagnosis, the majority of people who have brain tumors have died. Generally, a full brain image is created by a CT scan or MRI that is guided into the intracranial cavity. Some general risk factors and symptoms were found after researching a lot of statistical analysis focused on certain individuals affected by brain tumor. The advancement of technology in day-night science aims to establish new treatment methods. The doctor will visually examine this image for brain tumor identification and diagnosis. However, this specific technique determines the precision of the tumor stage & size and distinguishes the tumor stage from the tumor region. This study uses brain tumor segmentation based on algorithms based on k-means and fuzzy c-means. This technique enables tumor tissue segmentation with precision and reproducibility comparable to manual segmentation. In addition, the time for diagnosis is also decreased and the tumor stage of the given tumor region is established. Finally, implement a method using java to define a tumor stage that is simpler, cost-reducible, and time-saving.