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Added detailed mathematical equations for the Laplacian operator and its application in the detection of isolated points in image segmentation. Also included a function for determining isolated points based on response magnitude and threshold value. And added the section on the application of isolated point detection in X-ray image processing. |
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| title=2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings. |
chapter=On region merging: The statistical soundness of fast sorting, with applications |
publisher=IEEE | year=2003 | volume=2 | doi=10.1109/CVPR.2003.1211447 | pages=II:19–26 | isbn=0-7695-1900-8 }}</ref> such as [[color]], [[luminous intensity|intensity]], or [[Image texture|texture]]. Adjacent regions are significantly different color with respect to the same characteristic(s).<ref name="computervision" /> When applied to a stack of images, typical in [[medical imaging]], the resulting contours after image segmentation can be used to create [[3D reconstruction]]s with the help of geometry reconstruction algorithms like [[marching cubes]].<ref>Zachow, Stefan, Michael Zilske, and Hans-Christian Hege. "[https://opus4.kobv.de/opus4-zib/files/1044/ZR_07_41.pdf 3D reconstruction of individual anatomy from medical image data: Segmentation and geometry processing]." (2007).</ref>
== Applications ==
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