The picture below shows a grey matter mask segmented with FAST. ![]() For example, if three tissue types have been segmented, there will be three output datasets, one corresponding to each tissue class each dataset is a mask for each tissue type, and contains a fraction estimate at each voxel. However, if you are dealing with a subject that presents with a brain abnormality, such as a lesion, you may want to increase the number of classes to four in order to segment the lesion into its own class.įAST outputs a dataset for each tissue type. Often a researcher will want three tissue classes: White matter, grey matter, and cerebrospinal fluid (CSF). The tool is straightforward: Provide a skullstripped brain, decide how many tissue classes you wish to segment, and the rest of the defaults are usually fine. ![]() So goes the story of the creation of FAST. And then did the neuroscientists go down and slay the Canaanites, thirty thousand in number, and not a man survived as the neuroscientists did wade through swales of blood covered with the skins of their enemies and their eyes burned centroids of murder. With the terrible advent of FMRI did that all change now, the tissue of the brain, the seat of consciousness, could be blasted apart while leaving its host intact now could the grey be separated from the white, the gold from the dross. And the neuroscientists did curse and they did rage and they did utter blasphemy of such wickedness as to make the ears of Satan himself bleed. Numerous methods were attempted, as crude as they were unnatural - paint scrapers, lint rollers, zesters - but without success.
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