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            <c val="#008080">VISION AND SEGMENTATION</c>
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              <c val="#800080">Segmentation of the Brain</c>
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            <inlineAttr line-through="false">Segmentation of medical images, the process of visually differentiating between different areas, can be useful in many applications, such as locating tissues for radiation therapy, or measuring organs for diagnosis of disease. This example uses functions in the Image Processing Extension Pack to segment the brain from the rest of the cranial structures in an MRI cross-section of a head. </inlineAttr>
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            <inlineAttr line-through="false">We thank Professor David Haynor of the University of Washington for the image shown here.</inlineAttr>
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        <p style="Normal" margin-left="inherit" margin-right="inherit" text-indent="inherit" text-align="inherit" list-style-type="inherit" tabs="inherit">The approach used in this example is to construct a mask for just the brain tissue in the image. As a first step, the image is binarized. Upper and lower thresholds are adjusted visually until most of the brain is selected. Erosion can clean up the edges slightly, and create a mask that selects inside the region of interest, rather than preserving unwanted external details.</p>
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        <p style="Normal" margin-left="inherit" margin-right="inherit" text-indent="inherit" text-align="inherit" list-style-type="inherit" tabs="inherit">Since we applied erosion to the original image, we should now dilate to regain the original size:</p>
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        <p style="Normal" margin-left="inherit" margin-right="inherit" text-indent="inherit" text-align="inherit" list-style-type="inherit" tabs="inherit">This is our mask! Below we find its boundary and superimpose that on the original image to verify its correctness, and then we use the mask to view just the brain:</p>
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