Pathological Brain Image Segmentation and Classification: A Survey

Oncological diseases are getting immense importance in today's Health care scenario. Computational applications have critical role in medical applications. Accurate detection of abnormal mass in an early stage is essential for its treatment and hence increases the survival rate. Advanced Imaging Techniques play a great role to detect these abnormalities or tumour. But manual detection of these abnormalities or tumour especially in Magnetic Resonance Imaging (MRI) or Computed Tomography (CT) of brain may misdiagnose the result and give poor performance because of heterogeneous nature of tumour. Although many automated and semi automated methods are available to diagnose tumour but each has its own limitations and there is no final, state-of-the art technique to date which is able to be implemented in real scenario. This survey paper is based on techniques used to segment the normal and abnormal brain, analysis of their merits and demerits and their applications on advanced imaging techniques.