International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 02 Issue: 03 | June-2015 www.irjet.net p-ISSN: 2395-0072 © 2014, IRJET.NET- All Rights Reserved Page 1208 Pre-Processing Technique for Brain Tumor Detection and Segmentation Sheela.V.K 1 Dr. S. Suresh Babu, 2 1 Research Scholar, Department of Computer Science, Noorul Islam University, Tamilnadu, India 2 Professor, Department of Electronics and Communication TKM college of Engineering , Kerala, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract- Magnetic Resonance Imaging (MRI) is one of the power full visualization techniques, which is mainly used for the treatment of cancer. Magnetic Resonance Imaging is a radiation-based technique which represents the internal structure of the body in terms of intensity variation of radiated wave generated by the biological system when it is exposed to radio frequency pulses. Magnetic resonance imaging is used for the diagnosis of diseases related to soft tissues. When we interpret or inspect brain images, we should be aware of the image contrast, because all the information about the brain is mapped into intensity variation. The presences of materials which can affect the strong magnetic field can produce artifacts and intensity variation in the image. Artifacts are some extra features that are not related to original image. These features are introduced in the image during image acquisition. Artifacts and intensity variation affect the quality of analysis. So we need an efficient rectifying methodology for the removal of artifacts and intensity variation present in the image. Pre-processing techniques makes the image suitable for further processing; it enhances the quality of the image and finally removes the noise present in the Image. Pre-Processing techniques aim the enhancement of the image without altering the information content. Here we discuss most relevant and important pre-processing techniques for MRI images before dealing with brain tumour detection and segmentation. Keywords: Brain Tumor, Pre-processing, Segmentation, Image re-sampling, Skull Stripping, Contrast Enhancement, Noise Removal, Histogram Equalization 1. INTRODUCTION Magnetic Resonance Imaging (MRI) is one of the power full visualization techniques, which is mainly used for the treatment of cancer. Using MRI image technology, the internal structure of the body can be acquired in a safe and invasive way. Magnetic Resonance Imaging is a radiation-based technique; it represents the internal structure of the body in terms of intensity variation of radiated wave generated by the biological system, when it is exposed to radio frequency pulses. Magnetic Resonance Imaging is a very useful medical modality for the detection of brain abnormalities and tumor. It does not produce any damage to healthy tissue with its radiation, it provides high tissue information. Brain imaging allows a look into the brain and providing a detailed map of brain connectivity. Other major brain imaging methods are Diffusion Tensor Imaging (DTI), Position Emission Tomography (PET) and Event-Related Potential. Mainly MRI is used for identify the structural feature of the brain with high spatial resolution. The brain consists of cortical lobes, Sub-cortical structure and different tissues like Gray matter (GM), White matter (WM) and Cerebrospinal Fluid (CSF). When we interpret or inspect brain image, require careful consideration of the contrast, because all the information about the brain mapped into intensity variation. So we need pre-processing to remove extra marks and labels present in the image. Pre-processing techniques makes the image suitable for further processing, to enhance the image quality and finally pre –processing removes the noise present in the Image. 2. REVIEW ON PRE-PROCESSING TECHNIQUES The main causes of image imperfections are as follows 1. Low resolution 2. Simulation 3. Presence of image artifacts 4. Geometric Distortion 5. Low contrast 6. High level of noise The imperfections due to these are normally reduced through pre –processing methodologies.