Automatic Brain Tumor Tissue Detection based on Marker Controlled Watershed Segmentation in T1-weighted MR Images
Publication Date : 30/01/2018
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The brain tumor tissue detection allows localizing a mass of abnormal cells in a slice of Magnetic Resonance (MR). The automatization of this process is useful for post processing of the extracted region of interest like the tumor Segmentation. In order to detect this abnormal growth of tissue in an image, this paper presents a novel scheme which uses a two-step procedure; the marker controlled watershed algorithm and creating markers, gradient magnitude, and morphological operations. a bounding box is then automatically placed to delineate the region in which the tumor was found. Compared to the tumor delineation performed by an expert, a similarity measure of 91% was reached by using the Dice coefficient. The tests were carried out on 254 T1-weighted MRI images of 14 patients with brain tumors.
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