01921nas a2200157   4500008004100000245005700041210005400098260004200152300001600194520136600210100002801576700002201604700001701626700002701643856009301670       2002                        eng d00aA protocol-independent brain MRI segmentation method0 aprotocolindependent brain MRI segmentation method  aBellingham; WashingtonbSPIEc2002///  a1588 - 15993 aWe present a segmentation method that combines the robust,accurate, and efficient techniques of fuzzy connectedness with 
standardized MRI intensities and fast algorithms. The result is 
a general segmentation framework that more efficiently utilizes 
the user input (for recognition) and the power of computer (for 
delineation). This same method has been applied to segment brain 
tissues from a variety of MRI protocols. Images were corrected 
for inhomogeneity and standardized to yield tissue-specific 
intensity values. All parameters for the fuzzy affinity 
relations were fixed for a specific input protocol. Scale-based 
fuzzy affinity was used to better capture fine structures. Brain 
tissues were segmented as 3D fuzzy-connected objects by using 
relative fuzzy connectedness. The user can specify seed points 
in about a minute and tracking the 3D fuzzy-connected objects 
takes about 20 seconds per object. All other computations were 
performed before any user interaction took place. Segmentation 
of brain tissues as 3D fuzzy-connected objects from MRI data is 
feasible at interactive speeds. Utilizing the robust fuzzy 
connectedness principles and fast algorithms, it is possible to 
interactively select fuzzy affinity, seed point, and threshold 
parameters and perform efficient, precise, and accurate 
segmentations.
1 aNyúl, László, Gábor1 aUdupa, Jayaram, K1 aSonka, Milan1 aFitzpatrick, J Michael  uhttps://inf.u-szeged.hu/publication/a-protocol-independent-brain-mri-segmentation-method