Introduction - If you have any usage issues, please Google them yourself
that arises the surface coil array.
This entropy-based method does not require classification and
robustly addresses some problems that are more severe than
those found in brain imaging, including noise, steep bias field,
sensitivity of artery wall voxels to edge artifacts, and signal voids
near the artery wall. Validation studies were performed on a
synthetic digital phantom with realistic intensity inhomogeneity,
a physical phantom roughly mimicking the neck, and patient
carotid artery images. We compared LEMS to a modified fuzzy
c-means segmentation based method (mAFCM), and a linear
filtering method (LINF). Following LEMS correction, skeletal
muscles in patient images were relatively isointense across the field
of view. In the physical phantom, LEMS reduced the variation
in the image to 1.9 and across the vessel wall region to 2.5 ,
a value which should be sufficient to distinguish