Brain tumor Analysis is most challenging and emerging exploration area in Medical image processing. For appropriate regimen of Brain Tumor early detection and scrutiny is essential. To provide better detection of tumor without affecting a normal tissue is very difficult process. So we propose another novel technique for brain tumor detection through (MRI) Magnetic Resonance Imaging. Magnetic Resonance Imaging is a commonly processed method for providing high quality imaging. It provides higher details about the soft tissue of human anatomy. In this proposed method MR Image is preprocessed by Optimized Kernel Possibilistic C-Means Algorithm. Then image is enhanced by Adaptive DW-MTM filter. It helps to neglects the unwanted noise from the MR Imaging. Finally, the image is segmented by Region Growing Algorithm. Segmentation procedure is employs to split the tumor region from background. This segmented image is utilized for the detection and diagnoses of brain tumor in earlier stage. Key terms: - MR Imaging, Optimized Kernel Possibilistic C-Means Algorithm, Adaptive Double Window-Modified Trimmed Mean Filter, Region Growing Algorithm.

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