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This limitation might be overcome by using a more sophisticated active contour method [8, 9] that first identifies the outer bone structure of the LV based on local intensity information in a low dose CT (ldCT) image and subsequently partitions the LV between compact bone and bone marrow.
The initial selection of seed points throughout the image volume was chosen based on local intensity values.
In this study, we presented a vessel active contour model based on local intensity weighting and the vessel vector field.
This paper proposes a vessel active contour model based on local intensity weighting and a vessel vector field.
Aberration measurement based on local intensity variations with the amount of introduced aberrations therefore indicates an opposite (thus positive) coefficient for spherical aberration.
In this section, we describe the vessel active contour model based on local intensity weighting and the vascular vector field for vessel segmentation.
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Segmentation of CARc networks, ECM and arterial vessels: network-like structures were segmented using the Surface segmentation utility available in Imaris, which detects objects based on local intensities.
Images were then segmented into white/grey matter (WM/GM) tissues based on local and neighbouring intensities.
2D peaks are generated based on local maxima of the intensity as a function of m/z, centroid and assembled into 3D peak hills over the m/z-retention time plane.
In [30], the authors proposed a region-based active contour model based on local image fitting to extract the local image information, with respect to intensity inhomogeneity.
However, when necessary, the sampling intensity was increased based on local information needs.
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based on local eyewitness
based on local distance
based on local image
based on local practice
based on local property
based on local fee-for-service
based on average intensity
based on local history
based on local land
based on local expert
based on local feature
based on local currency
based on local well
based on local illumination
based on local produce
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