Medical imaging solution technology plays a vital role in the diagnosis and treatment of patients suffering from serious illness. In medical images, edge detection plays a vital role for recognition of the human organs. The performance of the edge detection determines the result of the processed image. Unfortunately, medical images like CT and MRI encounter a various number of noises such as Gaussian, Poisson and salt and pepper noise. Salt and pepper noise is frequently encountered in acquisition, transmission, and storage and processing of images. The presence of salt and pepper noise in an image may be either relatively high or low. Various filtering techniques have been proposed for removing salt and pepper noise. Conventional edge detection algorithms are belong to the high pass filtering which are not fit for noisy medical image edge detection because noise and edge belong to the scope of high frequency. In real world applications, medical images contain object boundaries, object shadows and noise. Therefore, they may be difficult to extract the edges in the presence of noise in medical images. Hence, a modified morphological edge detection algorithm is proposed to detect the edges in medical image. The performance of the proposed method is found to be better for detecting the edges and noise filtering than conventional techniques

MRI, Edge Detection, Morphology, Image Analysis, Brain Tumor

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