Maximum Intensity Projection (MIP) is a computer visualization method for 3D data that projects in the visualization plane the voxels with maximum intensity that fall in the way of parallel rays traced from the viewpoint to the plane of projection. This implies that two MIP renderings from opposite viewpoints are symmetrical images.
MIP is used for the detection of lung nodules in lung cancer screening programs which utilise computed tomography scans. MIP enhances the 3D nature of these nodules, making them stand out from pulmonary bronchi and vasculature.
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Segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics.
The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image (see edge detection). Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity, or texture. Adjacent regions are significantly different with respect to the same characteristic(s).
Here is a picture of segmentation of the Aorta lumen and aneuryism.
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